western michigan university computer center library program #1.1.4 calling name: stp prepared by: richard houchard* programmed by: richard houchard approved by: jack r. meagher date: september 1, 1974 statpack statistical package * with much assistance from nancy attwell, berenice houchard, george r. kohrman, charles lane jr., james e. nadonly, and delores vlahon PAGE 2 statpack purpose the statpack was written to enable a large section of the western michigan university community to do much of their own statistical analysis on a terminal with only a simple working knowledge of the decsystem-10. limitations maximum core allowable nv - number of variables no - number of observations no*nv+nv*nv+2*max+3*nv<8001 max - larger of nv or no see also table of variable-observation combinations. description statpack is an integrated, interactive package written for terminal use. it allows the user to issue simple commands for data analysis and will prompt him for necessary information. when questions of a procedural nature arise, the user may ask for an additional explanation by simply typing "help". the standard output device is the terminal; however, a command is available to channel output to the line printer, providing the user with the ability to obtain multiple copies. data input may be from terminal, disk, magnetic tape, or a structured data bank. input consists of observations each containing a value for every variable. variables are defined by a number or an alphabetic name of not more than five characters. data must be entered before issuing any of the statistical commands. once data has been entered, the statistical commands will continue analyzing it until the data is modified or replaced. options exist for evaluating data with missing values. it is also possible to restrict the data to only those observations where a certain set of circumstances occurs. statpack v4 PAGE 3 table of variable-observation combinations ------------------------------------------ the following is a table illustrating the various variable-observation data combinations that can be processed by statpack. letting the rows represent the number of observations and the columns represent the number of variables, one can easily determine if a specific variable-observation data combination is possible by simply determining the point where the variable line crosses the observation line. a "yes" indicates that the combination is possible; a blank indicates that statpack cannot analyze the amount of data necessary for that variable-observation combination. number of variables 1 2 3 4 5 10 15 20 25 30 40 50 75 100 10 yes yes yes yes yes yes yes yes yes yes yes yes yes 20 yes yes yes yes yes yes yes yes yes yes yes yes yes 30 yes yes yes yes yes yes yes yes yes yes yes yes 40 yes yes yes yes yes yes yes yes yes yes yes yes 50 yes yes yes yes yes yes yes yes yes yes yes yes 60 yes yes yes yes yes yes yes yes yes yes yes yes n 70 yes yes yes yes yes yes yes yes yes yes yes yes u 80 yes yes yes yes yes yes yes yes yes yes yes yes m 90 yes yes yes yes yes yes yes yes yes yes yes yes b 100 yes yes yes yes yes yes yes yes yes yes yes yes e 125 yes yes yes yes yes yes yes yes yes yes yes r 150 yes yes yes yes yes yes yes yes yes yes 200 yes yes yes yes yes yes yes yes yes yes o 250 yes yes yes yes yes yes yes yes yes f 300 yes yes yes yes yes yes yes yes 350 yes yes yes yes yes yes yes o 400 yes yes yes yes yes yes yes b 450 yes yes yes yes yes yes yes s 500 yes yes yes yes yes yes e 600 yes yes yes yes yes yes r 700 yes yes yes yes yes v 800 yes yes yes yes yes a 900 yes yes yes yes yes t 1000 yes yes yes yes yes i 1100 yes yes yes yes yes o 1200 yes yes yes yes n 1300 yes yes yes yes s 1400 yes yes yes 1500 yes yes yes 1600 yes yes 1700 yes yes 1800 yes yes 1900 yes yes 2000 yes statpack v4 PAGE 4 list of commands ---------------- "data" - data input by terminal "fetch" - read data from disk "form" - enter special input format "manip" - manipulate data in core (includes appending) "trans" - data transformations "store" - store data on disk "print" - print selected variables on line printer "type" - type selected variables on terminal "acbnk" - access a stored data bank "mabnk" - create a bank from data in stp "sort" - sort data into ascending order "mta/i" - read data from magtape "desc" - description of data - means, st. dev., var. "basic" - medians, modes, and ranges "erana" - std error of mean, coeff of skewness, coeff of var "estat" - "desc","basic", and "erana" "zscor" - z scores "kolm" - 1 or 2 sample kolmogorov-smirnov tests "corr" - correlation matrix "pcorr" - partial correlations "kendl" - kendall tau correlations "srank" - spearman rank correlation "ptbis" - point biserial correlation "ttest" - t test (significance between means) "corrt" - correlated t tests "mann" - mann-whitney u test "wilcx" - wilcoxon rank "anov1" - single factor analysis of variance "anov2" - 2-way analysis of variance "1wayr" - 1-way analysis of variance w/ repeated measures "anoc1" - 1-way analysis of covariance "regr" - regression "stepr" - stepwise regression "facto" - factor analysis "prob" - probability assoc. with t, f, or chi square "chisq" - chi square "cvsmt" - exponential curve smoothing model "plot" - scatter plot "hist" - histogram "bargr" - bar graph "freq" - frequency "xtab" - cross tab statpack v4 PAGE 5 "xtab*" - cross tab (table form - only if "assig" is used) "pcent" - percentiles "stop" - restart "help" - for commands "fini" - end run "info" - general information "assig" - assign output to line printer "deass" - reinitialize output to terminal "copys" - indicate more than 1 printer copy ("assig" and "print") "title" - label output with identification "name" - give names to variables "make" - make a text to be inserted into lineprinter output statpack v4 PAGE 6 program transfer ---------------- purpose: initiate the run of another program while in statpack description: stat pack may be used to transfer control to another program (initiate a run to a different program). as the following programs become available, they may be called directly from stat pack. bank freq tab corl regr when a call to another program is executed, the output file (if one has been created) is queued to the lineprinter, and the program specified is executed. to run a program type a "/" and the program name in response to "which command?". example: which command? /bank bank? statpack v4 PAGE 7 command: acbnk --------------- purpose: read data from a binary structured data bank. options are available to subset data, bypass observations which do not meet user specified criteria, and reject observations containing missing values. provisions have been made for variable names, and elimination of input formats. limitations: data must be in the form of a well-structured data bank. a maximum of 20 variables may be accessed at one time. description: the "acbnk" command is used to read data from a stored structured data bank located on the disk. when prompted, the user types the name of the bank (no extension is necessary; ".bnk" will automatically be added), and the project-programmer number enclosed in brackets (if other than his own), of the area where the file containing the bank is located. this is followed by the switches enclosed in parentheses, which are representative of the options available. if no options are desired, no options are necessary. options are: "i" - independent samples "m" - allow observations with missing data to be recovered "q" - select observations to be used by specifying criteria they must satisfy "s" - specify starting position next the user is asked to indicate which variables are to be read. bank codes (the number of the variable as situated in the bank) or variable names are typed in separated by commas. ranges of variables may be entered by typing the extremes of the range separated by a "-". if all variables are to be read use a "*". it should be noted that the first bank code specified becomes statpack's first variable, the second bank code the second variable, etc. thus, bank code 1 may end up as variable number 4. although the variable name obs is illegal, the user may indicate this variable both as a variable to be read and as a qualifier. the observation number will be referenced. in stp if obs is read as a variable it will be changed to obser. if no options are specified, data will be considered an observation at a time, starting with the first observation. if any of the variables to be recovered contain missing data for that observation, the entire observation is discarded. stp will continue in this manner, always checking the next observation, until either the entire bank has been considered or the data set whose size was specified at the beginning has been filled. statpack v4 PAGE 8 if an "s" switch is specified, the user will be asked to supply the starting observation number for the bank. any value between 1 and the number of the last observation in the bank may be used. this does not, however, inhibit the "acbnk" command from checking the entire bank for data. an "m" switch allows the collecting of samples containing missing data. the number "-9999e-20" will be used to denote values which are missing. the "q" switch specifies the qualifying option. by using the "q" switch, a user may select a subset of the bank where all the observations conform to a certain user-specified criteria. for example, data may be chosen where each observation in the data set is a male, less than 15 years old, with an i.q. of over 110. if the "q" switch has been specified, the user is instructed to type one qualifier after each "?". each qualifier consists of three parts: a variable, a relationship, and a value to be compared with the variable. hence, before each observation is included in the data set it must satisfy all the qualifiers specified. (for each observation to be accepted, the variable selected in each qualifier must have the indicated relationship to the value specified.) the relationships possible are: sign code alpha code relationship --------- ---------- ------------ "=" ",eq," or ".eq." equal "<>" or "><" ",ne," or ".ne." not equal ">" ",gt," or ".gt." greater than "<" ",lt," or ".lt." less than ">=" or "=>" ",ge," or ".ge." greater than or equal to "<=" or "=<" ",le," or ".le." less than or equal to the qualifier is constructed by typing the variable (either number or name), the sign code or alpha code, and finally the value. when the last qualifier has been entered, return and type a ^z(control z), a , or "stop"(the stop typed here simply terminates entry of the qualifiers, it is not the same as the "stop" command). the maximum number of qualifiers possible is 20 minus the number of variables selected for entry to the data set. it is not necessary to access a variable as data in order to use it as a qualifier. the "i" switch is used to assemble samples where variables in the same observation may not be related. for example, it is possible for variable 1 to be the i.q. of males and variable 2 the i.q. of females. each variable or set of variables is collected by looking through the entire data set once. when the last sample has been recovered, type a or a ^z(control z). all variables are forced to have the same number of observations. statpack v4 PAGE 9 examples (command explanations follow these examples): (1) which command? acbnk what bank name and switches? nick[220,220] list bank codes separated by commas case,2,3,weight,sex (2) which command? acbnk what bank name and switches? nick[220,220](s) what is the starting position? 123 list bank codes separated by commas case,2,3,weight,sex (3) which command? acbnk what bank name and switches? nick(q) list bank codes separated by commas case,sex,weight,7-11 a ? indicates a qualifier should be inserted. after last one type a ^z(control z), a , or stop ? sex=1 ? 2<>499.3 ? 3,gt,1.2 ? weight,ne,189 ? ^z (4) which command? acbnk what bank name and switches? rslt(qsm) what is the starting position? 121 list bank codes separated by commas iq,sex,weight a ? indicates a qualifier should be inserted. after last one type a ^z(control z), a , or stop ? iq>115 ? sex=1 ? weight<=210 ? ^z statpack v4 PAGE 10 (5) which command? acbnk what bank name and switches? nick(qi) independent samples will be taken on successive "list bank codes". when all independent samples have been given, type ^z(control z), a , or stop to the question independent sample 1 list bank codes separated by commas weight a ? indicates a qualifier should be inserted. after last one type a ^z(control z), a , or stop ? sex=1 ? age<24 ? ^z independent sample 2 list bank codes separated by commas weight a ? indicates a qualifier should be inserted. after last one type a ^z(control z), a , or stop ? sex=1 ? age>=24 ? ^z independent sample 3 list bank codes separated by commas weight a ? indicates a qualifier should be inserted. after last one type a ^z(control z), a , or stop ? sex=2 ? age<24 ? ^z independent sample 4 list bank codes separated by commas weight a ? indicates a qualifier should be inserted. after last one type a ^z(control z), a , or stop ? sex=2 ? age=>24 ? ^z independent sample 5 list bank codes separated by commas ^z statpack v4 PAGE 11 explanations: (1) read from data bank nick under area [220,220] the variables: case, 2, 3, weight, and sex. (2) read from data bank nick under area [220,220] the variables: case, 2, 3, weight, and sex beginning with observation 123 in the bank. (3) read from data bank nick the variables: case, sex, weight, and variable numbers 7 through 11; but only use those observations where the variable: sex is equal to 1, variable: 2 is not equal to 499.3, variable: 3 is greater than 1.2, and weight is not equal to 189. (4) read from data bank rslt the variables: iq, sex, and weight. starting at the bank's observation number 121 and using only those observations where the variable: iq is greater than 115, the variable: sex is equal to 1 and the variable: weight is less than or equal to 210. (5) read independent samples from bank nick, breaking the variable: weight into four variables each recovered as a separate sample where: each observation for sample 1 has the variable: sex equal to 1 and variable: age less than 24; each observation for sample 2 has the variable: sex equal to 1 and variable: age greater than or equal to 24; each observation for sample 3 has the variable: sex equal to 2 and variable: age less than 24; and each observation for sample 4 has the variable: sex equal to 2 and variable: age greater than or equal to 24. when finished there will be four separate variables each made up of a particular portion of the population. statpack v4 PAGE 12 command: anoc1 --------------- purpose: perform one way analysis of covariance limitations: the sum of the treatments and covariances must not exceed 20. reference: "statistical methods", snedecor and cochran, chapter 14. description: the "anoc1" command calculates analysis of covariance for one or more sets of data. the user will first be instructed to enter the options desired, separated by commas. available options are: "break"--rather than supplying a variable for each cell of the analysis of covariance, separate a single variable and one or more covariate variables into treatments based on values of a breakdown variable. "discr"--use values of the breakdown variable to form ranges, with each distinct value forming a separate range. (if this option is not used the user will be asked to enter ranges for the breakdown variable). "auto"--same results as "discr", however "auto" is not entered when the other options are entered, it is entered when asked for ranges. "range"--list ranges calculated. (only available if "discr" is used). if no options are specified, the user will be asked to enter the variables to be used as treatments. each variable entered becomes a separate treatment. variables may be entered by variable number or if names have been defined, as variable names. ranges of variables may be entered by typing the extremes of this range separated by a "-". next the user will be instructed to enter the number of covariates. for each treatment, the user will be asked to enter a variable to be used for each covariate. either variable numbers or variable names (if names have been defined) may be used. ranges of variables may be entered by typing the extremes of the range separated by a "-". no variable may be used as both a treatment and a covariate, and no variable may be used as two covariates. if "break" was specified as an option, the user will be instructed to enter the variables to be analysed. up to 20 statpack v4 PAGE 13 variables may be entered separated by commas. variables are indicated by variable number or variable name (if names have been defined for the variables). ranges of variables may be entered by typing the extremes of the range separated by a "-". for each variable specified, a separate analysis of covariance will be calculated. the user will then be asked to enter the breakdown variable. only one variable may be entered, by either variable number or variable name (if names have been defined). if option "discr" was not supplied then the user will be requested to enter the ranges for the breakdown variable. each range is entered on a separate line, minimum first, followed by a comma, and then the maximum. if names are to be given to the ranges, the user should enter a comma and the name (5 characters or less) following the maximum of the range. after the last range has been entered, type a control z (^z) or line feed. if the user wishes the ranges to be automatically created "auto" may be used. the user will now be instructed to enter covariates separated by commas. either variable numbers or variable names (if names have been defined) may be used. ranges of variables may be entered by typing the extremes of the range separated by a "-". the covariates will be broken into the same groups as the treatments. examples: which command? anoc1 list options separated by commas break,discr which variables are to be analysed? a which is the breakdown variable? 1 list covariates separated by commas b,c,d statpack v4 PAGE 14 ***** 1-way anocov ***** analysis on variable: a with treatments determined by a breakdown on variable: 1 ; covariates used: b , c , d unadjusted adjusted covariate means treat size mean mean b c d 1 4 62.4 62.9 14.7 1.38 -50.3 2 1 19.5 13.2 13.3 -35.9 123. 3 1 73.2 72.7 17.0 12.6 7.53 4 5 36.0 37.8 11.4 21.0 -11.5 5 9 34.3 35.1 10.8 -0.610 -36.2 6 12 39.1 39.5 8.02 2.88 17.9 7 21 43.5 43.2 11.2 -0.605 4.24 8 8 49.5 50.0 10.6 -4.49 -38.0 9 8 38.5 36.4 13.1 -7.31 43.1 10 4 31.8 32.4 6.50 0.949 16.4 *totals 0.304e+04 790. 13.2 -42.6 *average 41.7 10.8 0.180 -0.583 *beta weights 0.217 -0.798e-01 0.234e-01 1 way anocov source sum of squares df mean squares f prob between adjusted 5033.185 9 559.2 0.741 .670 treatments error 45262.61 60 754.4 total 50295.79 69 statpack v4 PAGE 15 which command? anoc1 list options separated by commas list variables to be used as treatments d,f how many covariates? 2 list covariates for var: d a,b list covariates for var: f c,e ***** 1-way anocov ***** treatments and covariates are individual variables treat cov 1 cov 2 d a b f c e unadjusted adjusted covariate means treat size mean mean cov 1 cov 2 d 73 -0.583 -4.43 41.7 10.8 f 73 6.86 10.7 0.180 24.8 *totals 458. 0.306e+04 0.260e+04 *average 3.14 20.9 17.8 *beta weights 0.799e-01 -0.314 1 way anocov source sum of squares df mean squares f prob between adjusted 3998.871 1 3999. 0.394 .531 treatments error 1440020. 142 0.1014e+05 total 1444019. 143 statpack v4 PAGE 16 command: anov1 --------------- purpose: calculate one way analysis of variance reference: "statistical principles in experimental design", winer, pages 96-102. description: the "anov1" command allows the user to calculate one-way analysis of variance. the user will first be instructed to list the options desired separated by commas (if no options are desired type a ). possible options are: "break"--select samples from one variable based on the value of a second variable. for each observation, the value of the second variable (breakdown variable) will be used to determine in which sample the variable being analyzed belongs. this is accomplished by determining which of a series of ranges the value of the breakdown variable fits into, and then moving the value of the analysis variable to the corresponding sample. (if this option is not used, the analysis will be done using variables as the samples.) note: the following options are to be used only if "break" has been used. "discr"--automatic breakdown. instead of the user entering ranges, a separate range will be created automatically for each value in the breakdown variable. "auto"--automatic breakdown. this option is the same as the "discr" option. do not enter "auto" with the other options; it should be entered only when asked to type in the ranges. the "discr" and "auto" options are equivalent. the only difference is at which point in the program they are entered. note: the following option is available only if automatic breakdowns are to be used. "range"--list the ranges to be used for the automatic breakdown. if the "break" option has not been specified, the analysis of variance will be calculated with each variable specified by the user occupying a single cell. when instructed the user lists the variables to be used in the analysis of variance separated by commas. up to 30 variables may be indicated by variable names (if names have been defined) or variable numbers. ranges of variables may be entered by listing the extremes of the range statpack v4 PAGE 17 separated by a "-". one or more "*" may be used when listing the variables to be analyzed. one at a time each variable not yet specified in the analysis will be substituted for every "*". those cases where the same variable would be listed twice in the same analysis will be eliminated, as will be those cases that except for a switch in the order of variables, duplicate an analysis already performed. if the "break" option has been used, it will be necessary for the user to supply the following information: (1) the variables for which analysis of variance are to be calculated (up to 20). the samples for each set of analysis of variance will be selected from a single variable. variables may be listed using either variable names (if names have been defined) or variable numbers. ranges of variables may be specified by listing the extremes of the ranges separated by a "-". where analysis of variances are to be calculated for all variables, a "*" may be used instead of variable names or numbers. (2) the variable to be used for the breakdowns. only one variable may be entered, specified by either its variable name (if the name has been defined) or variable number. all variables listed for analysis will be processed using the same breakdown variable. (3) ranges for the breakdown variable. if the "discr" option has been used, this information will be automatically calculated, and need not be supplied by the user. if the "discr" option has not been used, the user may still request the ranges to be automatically calculated by responding with "auto". to specify ranges, the user types the extremes of the range, smaller first, separated by a comma. only one range may be entered per line. up to 50 ranges may be specified. after the last range has been entered, the user types a ^z(control z). statpack v4 PAGE 18 examples: which command? anov1 list options separated by commas which variables? test1,test2,test3,test4 ***** 1-way anova ***** tret. size mean std. dev. test1 559 41.75 21.73741 test2 559 49.68 18.73237 test3 559 47.88 12.27697 test4 559 64.81 19.69569 source sum of sq. d.f. mean sq. f prob between 160902.1 3 .5363e+05 157.5 0.0000 within 760030.1 2232 340.5 total 920932.1 2235 which command? anov1 list options separated by commas break which variables are to be analyzed? gpa what is the breakdown variable? weight enter ranges for breakdown variable: weigh ? 100,120,low ? 121,150,med ? 151,200,high ? ^z ***** 1-way anova ***** analysis on variable: gpa with treatments determined by a breakdown on variable: weigh tret. size mean std. dev. low 25 2.918 0.5476086 med 29 3.002 0.5271557 high 34 2.958 0.5200980 source sum of sq. d.f. mean sq. f prob between 0.9464264e-01 2 .4732e-01 0.1683 0.8454 within 23.90458 85 .2812 total 23.99922 87 statpack v4 PAGE 19 which command? anov1 list options separated by commas break,discr,range which variables are to be analyzed? gpa what is the breakdown variable? age breakdown ranges for variable: age 22.00 , 22.00 23.00 , 23.00 24.00 , 24.00 ***** 1-way anova ***** analysis on variable: gpa with treatments determined by a breakdown on variable: age tret. size mean std. dev. 1 39 2.914 0.4997773 2 26 2.798 0.4729230 3 35 3.015 0.4958847 source sum of sq. d.f. mean sq. f prob between 0.7007980 2 .3504 1.450 0.2397 within 23.44360 97 .2417 total 24.14440 99 statpack v4 PAGE 20 command: anov2 --------------- purpose: calculate two-way analysis of variance. reference: "topics in intermediate statistical methods", snedecor and cochran, pages 104-106. description: the "anov2" command allows the user to calculate two- way analysis of variance. the user will first be instructed to list the options desired separated by commas (if no options are desired type a ). possible options are: "headr"--eliminate means and standard deviation report. "break"--select samples from one variable based on the value of two other variables. for each observation, the value of the two variables (breakdown variables) will be used to determine in which cell the variable being analyzed belongs. this is accomplished by determining which of a series of ranges each breakdown variable fits into, and then moving the value of the analysis variable to the corresponding cell. (if this option is not used, variables will be used as cells). note: the following options are to be used only if the "break" option is specified. "discr"--establish ranges for the breakdown variables automatically. rather than the user typing in ranges for the breakdown variables, ranges will be automatically calculated for each breakdown variable in the following manner: 1) if a breakdown variable has fewer discrete values than defined groups, a range will be calculated for each value of the breakdown variable. 2) if a breakdown variable has more discrete value than defined groups, a range will be calculated by finding the difference between the maximum and minimum values of the breakdown variable and separating the difference into ranges; so that there is a range for each defined group and all the ranges have equal intervals. "auto"--if the "discr" option has not been used and the user wishes to have ranges created automatically for a breakdown variable, he may type "auto" when instructed to enter the ranges for a particular breakdown variable. ranges will be calculated in the same manner as for "discr". do not enter "auto" with the other options; it should be entered only when instructed to type in the ranges. statpack v4 PAGE 21 "group"--specify number of groups (used when groups are to be automatically broken down). preset to a maximum of 20. note: the following is available only if automatic breakdowns are used. "range"--list the ranges to be used for automatic breakdown. if the "break" option has not been specified, the analysis of variance will be created with each specified variable occupying a cell. the user will be asked for the following information: 1) number of levels for factor 1. any number between 1 and 20 is acceptable. 2) number of levels for factor 2. any number between 1 and 20 is acceptable. 3) the variable to be put in each cell. one at a time the user will be asked to specify which variable to be put into each cell. either the variable name (if names have been defined) or the variable number may be used to indicate the variable. if a cell is empty the user may indicate this by typing "empty". a "*" may also be used in one or more cells. one at a time each variable not yet specified in the analysis will be substituted for every "*". if the break option has been specified, it will be necessary for the user to supply the following information: 1) if the "group" option has been selected, the user will be asked to indicate how many groups comprise a breakdown variable. each breakdown variable can have 1 to 20 groups. 2) the variables for which the analyses are to be performed for each two-way analysis of variance, the values comprising all the cells will be selected from the same variable. up to 40 variables may be entered using either variable names (if names have been defined) or variable numbers. ranges of variables may be specified by listing the extremes of the ranges separated by a "-". where analysis of variance are to be calculated for all variables, a "*" may be used instead of variable numbers or names. 3) the user will be asked to supply both breakdown variables. either variable names (if names have been defined) or variable numbers may be used. 4) if the "discr" option was not specified, the user will be expected to enter the ranges for the breakdowns. up to 20 ranges may be submitted. each range is indicated by typing the extremes (smaller first) separated by a comma. when finished entering ranges for either of the breakdown variables, type a ^z(control z). if ranges are to be calculated automatically for a breakdown variable, type "auto". statpack v4 PAGE 22 examples: which command? anov2 list options separated by commas how many cells in factor 1? 2 how many cells in factor 2? 2 type in each variable after the corresponding level, "empty"-indicates empty cell cell( 1, 1)? test1 cell( 1, 2)? test2 cell( 2, 1)? test3 cell( 2, 2)? test4 *****2-way anova***** factor one factor two level 1 2 1 n 100.00 100.00 mean 39.00 47.37 stdv 21.09 20.28 2 n 100.00 100.00 mean 45.96 62.21 stdv 12.00 19.20 preliminary anova source df ss ms f prob cells 3 28581.45 9527.15 27.84 .0000 1 ignoring 2 1 11878.98 2 ignoring 1 1 15150.97 within 396 135500.27 342.17 total 399 164081.73 final anova source df ss ms f prob cells 3 28581.45 1 eliminating 2 1 11878.98 11878.98 34.72 .0000 2 eliminating 1 1 15150.96 15150.96 44.28 .0000 1 by 2 1 1551.51 1551.51 4.53 .0338 within 396 135500.27 342.17 total 399 statpack v4 PAGE 23 which command? anov2 list options separated by commas break which variables are to be analyzed? gpa which variable is breakdown variable 1? height which variable is breakdown variable 2? weight list the ranges for breakdown variable: heigh 50,62 63,64 65,70 ^z list the ranges for breakdown variable: weigh 100,118 119,137 138,200 ^z *****2-way anova***** analysis run on variable: gpa with cells determined by breakdowns on variable: heigh and variable: weigh factor one factor two level 1 2 3 1 n 11.00 11.00 5.00 mean 2.95 2.86 3.11 stdv 0.47 0.58 0.29 2 n 8.00 9.00 13.00 mean 2.89 2.80 3.15 stdv 0.66 0.59 0.56 3 n 1.00 3.00 25.00 mean 2.90 3.18 2.90 stdv 0.00 0.45 0.52 preliminary anova source df ss ms f prob cells 8 1.18 0.15 0.51 .8490 1 ignoring 2 2 0.03 2 ignoring 1 2 0.25 within 77 22.47 0.29 total 85 23.64 statpack v4 PAGE 24 final anova source df ss ms f prob cells 8 1.18 1 eliminating 2 2 0.18 0.09 0.32 .7296 2 eliminating 1 2 0.40 0.20 0.68 .5085 1 by 2 4 0.75 0.19 0.64 .6359 within 77 22.47 0.29 total 85 which command? anov2 list options separated by commas break,discr,range which variables are to be analyzed? gpa which variable is breakdown variable 1? sex which variable is breakdown variable 2? age breakdown ranges for variable: sex .0000 , .0000 1.000 , 1.000 breakdown ranges for variable: age 21.00 , 21.00 22.00 , 22.00 23.00 , 23.00 *****2:way anova***** analysis run on variable: gpa with cells determined by breakdowns on variable: sex and variable: age factor one factor two level 1 2 3 1 n 18.00 16.00 11.00 mean 2.90 2.80 2.74 stdv 0.47 0.45 0.46 2 n 17.00 23.00 15.00 mean 2.86 2.99 2.84 stdv 0.51 0.52 0.49 statpack v4 PAGE 25 preliminary anova source df ss ms f prob cells 5 0.67 0.13 0.55 .7370 1 ignoring 2 1 0.18 2 ignoring 1 2 0.21 within 94 22.70 0.24 total 99 23.37 final anova source df ss ms f prob cells 5 0.67 1 eliminating 2 1 0.18 0.18 0.76 .3861 2 eliminating 1 2 0.22 0.11 0.45 .6413 1 by 2 2 0.27 0.13 0.56 .5746 within 94 22.70 0.24 total 99 statpack v4 PAGE 26 command: assign ---------------- purpose: assign output to the line printer. description: the "assign" command allows the user to print results on the line printer. this command must be given prior to any commands for which the output is to be assigned to the line printer. once the command has been given, no other responses are necessary. output will remain assigned to the line printer until a "deass" command is given. it is permissible to channel output back and forth between the line printer and terminal using the "assign" and "deass" commands. questions to the user will still be asked via the terminal. while output is assigned, no output will appear on the terminal. note: a "fini" command must be used to initiate printing of the output assigned to the line printer. it is necessary to use the "fini" command to ensure printing of the results which were assigned. for multiple copies of the results use the "copys" command. example: which command? assign output assigned to printer which command? statpack v4 PAGE 27 command: bargr --------------- purpose: create bargraphs reference: "basic statistical methods", downe and heath, page 27. description: the "bargr" command allows user to construct one or more bargraphs. when instructed, the user enters the variables separated by commas for which the bargraphs are to be created. up to 20 variables may be entered using either the variable names (if names have been defined) or variable numbers. ranges of variables may be indicated by typing the extremes of the range separated by a "-". where bargraphs are to be constructed for all variables, a "*" may be used in place of variable names or numbers. the user will next be instructed to enter the ranges for the bargraphs. ranges are entered 1 per line, minimum first, followed by a comma and the maximum. when the last range has been entered, a control z (^z) or a blank line should be typed. ranges may be calculated automatically, by placing each unique value in an individual range, or if more than 40 values exist, then 40 ranges are created each with an equal interval. to have the ranges automatically calculated the user should respond with "auto" when instructed to enter the ranges. if auto is used, and the user wishes to limit the number of ranges to be created, the "auto" should be followed by a "/" and the maximum number of ranges the user desires. examples: which command? bargr which variables? grade enter ranges 1 per line ? 2,2 ? 3,3 ? 4,4 ? 5,5 ? 6,6 ? 7,7 ? statpack v4 PAGE 28 ***** bar graph for variable: grade ***** range of values freq pcent +----+----+----+----+ 2.000 - 2.000 0 0.0 i 3.000 - 3.000 2 5.7 ixxx 4.000 - 4.000 7 20.0 ixxxxxxxxxx 5.000 - 5.000 10 28.6 ixxxxxxxxxxxxxx 6.000 - 6.000 11 31.4 ixxxxxxxxxxxxxxxx 7.000 - 7.000 5 14.3 ixxxxxxx ---- +----+----+----+----+ 35 ^ ^ ^ ^ 10.0 20.0 30.0 40.0 percentage which command? bargr which variables? 2,3 enter ranges 1 per line ? auto/4 ***** bar graph for variable: grade ***** range of values freq pcent +----+----+----+----+ 3.000 - 4.000 2 5.7 ixx 4.000 - 5.000 7 20.0 ixxxxxxx 5.000 - 6.000 10 28.6 ixxxxxxxxxx 6.000 - 7.000 16 45.7 ixxxxxxxxxxxxxxx ---- +----+----+----+----+ 35 ^ ^ ^ ^ 15.0 30.0 45.0 60.0 percentage ***** bar graph for variable: iq ***** range of values freq pcent +----+----+----+----+ 42.00 - 75.00 8 22.9 ixxxxxxxxxxx 75.00 - 107.0 14 40.0 ixxxxxxxxxxxxxxxxxxxx 107.0 - 139.0 10 28.6 ixxxxxxxxxxxxxx 139.0 - 172.0 3 8.6 ixxxx ---- +----+----+----+----+ 35 ^ ^ ^ ^ 10.0 20.0 30.0 40.0 percentage statpack v4 PAGE 29 command: basic --------------- purpose: displays medians, modes, and ranges. reference: "basic statistical methods", downe and heath, pages 32-34. description: the "basic" command enables the user to display medians, modes, and ranges for all variables. once the command has been given no additional responses are necessary. output will be appropriately labeled. example: which command? basic var. median mode maximum minimum sex 1.000000 1.000000 1.000000 0.0000000 age 23.00000 22.00000 27.00000 18.00000 heigh 64.00000 66.00000 73.00000 58.00000 weigh 139.0000 112.0000 251.0000 86.00000 iq 101.0000 113.0000 129.0000 70.00000 gpa 3.050000 2.910000 3.790000 1.850000 statpack v4 PAGE 30 command: chisq --------------- purpose: calculate chi square limitation: chisq will only calculate the chi square for raw data already entered into statpack. there are no provisions for calculating a chi square from a pre-calculated table. reference: "non-parametric statistics", siegel, pages 42-47, 104-111, 196-202. description: the "chisq" command allows the user to calculate either a one-variable or a two-variables chi square. options exist to group certain values together prior to forming the contingency table, and collapsing the table once it is formed. when instructed to list the options, the user enters the options desired separated by commas (if no options are desired, type a ). possible options are: group--group certain ranges of values together prior to forming the contingency table contg--eliminate contingency table from final output colps--collapse contingency table (includes omitting) fishr--calculate fishers exact probability (2x2 table only) when instructed to enter variables, the user enters either one or two variables separated by a comma. variables may be listed by variable names (if names have been defined) or variable numbers. if a one-variable chi square is desired for all variables, the user may enter a "*". similarly, a two-variable chi square between a single variable and all the remaining variables may be entered by typing the variable which is to be analyzed with all others, a comma, and a "*". if two variable chi squares are to be calculated between all combinations of variables, a "*,*" may be used. if the "group" option has been given, the user will be allowed to enter ranges for grouping certain values together. up to 15 ranges may be entered for each variable, one range per line. each range is entered by typing the extremes of the range, smaller first separated by a comma. to finish entering ranges, type a "stop" (this stop terminates the entry of ranges - it is not the same as the "stop" command), , or ^z(control z). if the "colps" option has been given, the user will be expected to enter instructions for collapsing the contingency table. each instruction is composed of a single character indicating what is to be done, a variable name (if names have statpack v4 PAGE 31 been defined) or variable number enclosed in parentheses, and a string of numbers referencing levels to be acted upon. single letter codes possible are: c--combine levels d---delete levels the variable enclosed in parentheses must be one of the variables being analyzed. the string of numbers represent the level numbers in the contingency table which are to be acted upon. ranges of levels may also be indicated by entering the extremes of the range separated by a "-". collapsing instructions are entered one per line. when finished, type "stop" or ^z(control z). the probability and contingency coefficient will be supplied with the chi square. in the case of a 2 x 2 table the corrected chi square will also be calculated. if in a two variable chi square only one level exists for either of the variables, the chi square will be calculated as a one-variable test. examples: which command? chisq list options separated by commas which variable or variables? sex,age ***** chi square ***** levels for horizontal variable: sex level values comprising level 1 .0000 2 1.000 levels for vertical variable: age level values comprising level 1 18.00 2 19.00 3 20.00 4 21.00 5 22.00 6 23.00 7 24.00 8 25.00 9 26.00 10 27.00 statpack v4 PAGE 32 sex level 1 2 total age .................... 1 . 27 18 45 2 . 28 21 49 3 . 23 35 58 4 . 36 28 64 5 . 30 36 66 6 . 22 30 52 7 . 26 38 64 8 . 30 34 64 9 . 25 29 54 10 . 34 25 59 total . 281 294 575 chi square = 11.94035 with 9 degrees of freedom having a probability of 0.22 contingency coefficient = 0.47979e-01 which command? chisq list options separated by commas help the chi square command operates from raw data not pre calculated tables, options available are: "group" - used to establish groupings prior to colps "contg" - used to eliminate contingency table from final output "colps" - collapse contingency table (includes omitting) "fishr" - fisher's exact test probability (2x2 only) if no options are desired type a return list options separated by commas group which variable or variables? height,weight enter ranges, 1 per line for variable: heigh ?58,65 ?66,73 ? ^z enter ranges, 1 per line for variable: weigh ?100,150 ?151,235 ? ^z statpack v4 PAGE 33 ***** chi square ***** levels for horizontal variable: heigh level values comprising level 1 58.00 , 59.00 , 60.00 , 61.00 , 62.00 , 63.00 , 64.00 , 65.00 2 66.00 , 67.00 , 68.00 , 69.00 , 70.00 , 71.00 , 72.00 , 73.00 levels for vertical variable: weigh level values comprising level 1 100.0 , 102.0 , 104.0 , 106.0 , 108.0 , 110.0 , 112.0 , 114.0 , 116.0 , 118.0 , 120.0 , 122.0 , 124.0 , 126.0 , 128.0 , 131.0 , 133.0 , 135.0 , 137.0 , 139.0 , 141.0 , 143.0 , 145.0 , 147.0 , 149.0 , 2 151.0 , 153.0 , 155.0 , 157.0 , 159.0 , 161.0 , 163.0 , 165.0 , 167.0 , 169.0 , 171.0 , 173.0 , 175.0 , 177.0 , 180.0 , 182.0 , 184.0 , 186.0 , 188.0 , 190.0 , 192.0 , 194.0 , 196.0 , 198.0 , 200.0 , 202.0 , 204.0 , 206.0 , 208.0 , 210.0 , 212.0 , 214.0 , 216.0 , 218.0 , 220.0 , 222.0 , 224.0 , 227.0 , 229.0 , 235.0 heigh level 1 2 total weigh ................... 1 . 278 31 309 2 . 75 146 221 total . 353 177 530 chi square = 181.8592 with 1 degrees of freedom corrected chi square = 179.3489 having a probability of 0.00 contingency coefficient = 0.5028279 statpack v4 PAGE 34 which command? chisq list options separated by commas colps which variable or variables? age levels for variable: age level values comprising level 1 18.00 frequency = 45 2 19.00 frequency = 49 3 20.00 frequency = 58 4 21.00 frequency = 64 5 22.00 frequency = 66 6 23.00 frequency = 52 7 24.00 frequency = 64 8 25.00 frequency = 64 9 26.00 frequency = 54 10 27.00 frequency = 59 collapsing portion insert 1 instruction per line after the ? ? c(age)1,3,5 ? d(age)2,9 ? c(age)6-10 ? ^z statpack v4 PAGE 35 ***** chi square ***** levels for variable: age level values comprising level 1 18.00 , 20.00 , 21.00 , 22.00 frequency = 233 2 23.00 , 24.00 , 25.00 , 27.00 frequency = 239 chi square = 0.7627119e-01 with 1 degrees of freedom having a probability of 0.78 statpack v4 PAGE 36 command: copys --------------- purpose: obtain multiple copies of output. limitation: maximum of 63 copies description: the "copys" command allows the user to obtain multiple copies of output. when requested, the user types in the number of copies desired. up to 63 copies may be requested. if the number entered is less than or equal to zero, the number of copies will default to one. the "copys" command is used in conjunction with the "print" and "assign" commands. it may be issued at anytime prior to either the "print" command (for a printing of the data) or the "fini" command (for the output that was assigned to the line printer). once the number of copies has been entered, it can only be changed by another "copys" command. example: which command? copys how many output copies? 3 statpack v4 PAGE 37 command: corr -------------- purpose: compute the correlation matrix for all variables. reference: "basic statistical methods", downe and heath, pages 78-90. description: the "corr" command displays the computed correlation matrix for all variables in the data set. only the lower triangular portion of the correlation matrix will be displayed, adjusting the number of correlations per line to fully utilize the area available for the output. no responses are necessary once the command has been given. output will be labeled with variable names, if they have been defined; otherwise numbers will be used. example: which command? corr ***** correlation matrix ***** var. scor1 1.0000 2 0.5349 1.0000 index 0.2720 0.4078 1.0000 lengt 0.0895 0.1050 0.0612 1.0000 5 0.0718 -0.4686 -0.4367 -0.0507 1.0000 scor1 2 index lengt 5 statpack v4 PAGE 38 command: corrt --------------- purpose: calculate correlated t tests reference: "statistical methods", snedecor and cochran, pages 92-97. description: the "corrt" command allows the user to calculate correlated t tests for all combinations of variables. after the command is given, no other user responses are necessary. output will be labeled with variable names (if names have been defined) or variable numbers. results will be adjusted to fully utilize space available for output. example: which command? corrt ***** correlated t ***** iq 0.0000 test1 -25.22 0.0000 test2 -25.27 3.030 0.0000 test3 -31.13 6.117 -0.8085 0.0000 test4 -54.33 9.795 5.702 8.523 0.0000 iq test1 test2 test3 test4 statpack v4 PAGE 39 command: cvsmt --------------- purpose: forecasting reference: "decision rules for inventory management", r. g. brown. description: the "cvsmt" command utilizes an exponential smoothing model in forecasting cases, where time is the independent variable and assumed the only condition changing. the user will first be instructed to enter the variables separated by commas for which forecasts are to be made. up to 20 variables may be listed, by variables names (if names have been defined) or variable numbers. ranges of variables may be specified by typing the extremes of the range separated by a "-". if forecasts are to be made for all variables the user may respond with a "*". the user will next be instructed to enter options separated by commas. possible options are: "nlogy"--natural log transformation of dependent variable (for each observation the natural log of the variable will be used in the calculations). "nlogt"--natural log transformation of time "trend"--user enters trend line "short"--short output (trend line, variance, projected values) "multi"--multiplicative rather than additive seasonal terms if no options are desired type a . the user will now be told to enter the number of observations per cycle. at least two cycles of data must be present to establish a forecasting model. next the user will be asked to enter the weighting factors. one at a time he will be prompted for the trend, steady state, and seasonal factors. finally the user will be instructed to enter the percentage criteria for seasonal terms. those periods that consistently deviate from the expected values by this percentage in the first two cycles are assumed to have seasonal effects. if the user has specified the "trend" option he will also be instructed to enter the trend line. this is accomplished by typing first the y intercept and then the slope when prompted. statpack v4 PAGE 40 example: which command? cvsmt which variables? 1 list options separated by commas how many observations per cycle? 8 weighting factors for: steady state? .1 trend? .1 seasonal? .05 how many periods to be projected? 16 what is the percentage criterion for seasonal terms? 25% ***** curve smoothing model ***** for variable: 1 , with add. seasonal terms percentage criterion for seasonal terms is 25.0% weighting factors were: 0.100 for steady state 0.100 for trend, and 0.050 for seasonal the trend line is y= 4.560484 + 0.4747067e-01x actual predicted deviation % deviation mean avg dev. 1 6.000 6.000 0.0000 0.0000 0.0000 2 7.000 7.000 -0.5960e-07 0.8515e-06 0.2980e-07 3 2.000 2.000 -0.5960e-07 0.2980e-05 0.3974e-07 4 1.000 1.000 -0.4470e-07 0.4470e-05 0.4098e-07 5 5.000 4.798 0.2022 4.214 0.4043e-01 6 3.000 4.868 -1.868 38.37 0.3450 7 7.000 6.819 0.1812 2.657 0.3216 8 6.000 4.742 1.258 26.52 0.4386 9 8.000 6.304 1.696 26.91 0.5783 10 7.000 7.300 -0.2995 4.104 0.5504 11 3.000 2.295 0.7045 30.69 0.5644 12 3.000 1.291 1.709 132.3 0.6598 13 1.000 5.085 -4.085 80.33 0.9233 14 6.000 4.679 1.321 28.23 0.9517 15 8.000 6.943 1.057 15.22 0.9587 16 9.000 4.843 4.157 85.84 1.159 17 6.000 6.793 -0.7927 11.67 1.137 18 7.000 7.703 -0.4027 9.123 1.113 19 4.000 2.763 1.237 44.78 1.119 20 2.000 1.823 0.1772 9.720 1.072 21 6.000 5.545 0.4549 8.204 1.043 22 1.000 5.652 -4.652 82.31 1.207 23 7.000 7.372 -0.3717 5.042 1.171 24 8.000 5.218 2.782 53.32 1.238 25 8.000 6.977 1.023 14.67 1.229 statpack v4 PAGE 41 26 7.000 7.877 -0.8769 11.13 1.216 27 4.000 3.020 0.9802 32.46 1.207 28 5.000 2.013 2.987 148.4 1.271 29 6.000 5.712 0.2881 5.043 1.237 30 5.000 5.787 -0.7868 13.60 .1222 31 6.000 7.897 -1.9897 24.02 1.243 32 7.000 5.784 1.216 21.01 1.243 33 7.445 34 8.257 35 3.500 36 2.601 37 6.158 38 6.208 39 8.314 40 6.309 41 7.847 42 8.660 43 3.903 44 3.003 45 6.560 46 6.611 47 8.717 48 6.711 variance is 3.070 statpack v4 PAGE 42 command: data -------------- purpose: enter data from terminal. description: the "data" command allows users to enter data by terminal according to a standard or user specified format. with standard format, the user enters values separated by commas with a maximum of 20 values per line. if 20 values will not fit on one line, use the "form" command prior to "data". data is entered by observation, the first value being variable 1, the second value, variable 2, etc. when finished typing the last observation, type a ^z(control z). example: which command? data how many input variables? 3 enter input data 1,2,3 6,5,4 7,6.5,3 2,4,8 2.0,3.0,4.5 2,3,4 6,1,8 ^z statpack v4 PAGE 43 command: deass --------------- purpose: reassign output to terminal from line printer. description: the "deass" command allows the user to reassign output to the terminal. once the command has been given, no other user responses are necessary. this command is used in conjunction with the "assign" command. it is permissible to channel output back and forth between the line printer and terminal using the "assign" and "deass" commands. example: which command? deass output assigned to terminal statpack v4 PAGE 44 command: desc -------------- purpose: calculate the mean, standard deviation, and variance for all variables. reference: "statistical methods", snedecor and cochran, pages 44-46. description: the "desc" command displays the mean, standard deviation, and variance of all variables in the data set. after the command has been given no other user responses are necessary. output will be appropriately labeled, with variable names, if they have been defined; otherwise, numbers will be used to label the variables. example: which command? desc there are 5 variables and 23 observations var. means std.dev. variance scor1 3.000000 3.089572 9.545455 2 4.217391 1.953005 3.814229 index 3.782609 3.029499 9.177866 lengt 5.478261 2.793980 7.806324 5 5.695652 2.457545 6.039526 statpack v4 PAGE 45 command: erana --------------- purpose: determine the standard error of the mean, the coefficient of skewness, and the coefficient of variation. reference: "statistical methods", snedecor and cochran, pages 50, 62-63, 86. description: the "erana" command enables the user to display the standard error of the mean, the coefficient of skewness, and the coefficient of variation for all variables. once the command has been given, no additional responses are necessary. output will be appropriately labeled. example: which command? erana var. std err of mean skewness coef. of var. sex 0.2088243e-01 -0.4522899e-01 97.84924 age 0.1160092 -0.3795715e-01 12.26888 heigh 0.1330046 0.4152664 4.981309 weigh 1.382710 0.5287957 23.29064 iq 0.7284885 -0.9540812e-01 17.29185 gpa 0.2106721e-01 -0.2985082 16.89175 statpack v4 PAGE 46 command: estat --------------- purpose: incorporates the commands "desc", "basic", and "erana" into one command. description: the "estat" command combines the "desc", "basic", and "erana" commands into one command, allowing the user to obtain the following statistics: means, standard deviations, variances, medians, modes, maximums, minimums, standard error of the means, coefficients of skewness, and coefficient of variation for all variables. no additional responses are necessary after the command has been given. example: which command? estat there are 6 variables and 575 observations var. means std.dev. variance sex 0.5113043 0.5003074 0.2503075 age 22.65391 2.779382 7.724963 heigh 63.97043 3.186565 10.15419 weigh 142.2348 33.12739 1097.424 iq 100.9339 17.45335 304.6193 gpa 2.988052 0.5047344 0.2547569 var. median mode maximum minimum sex 1.000000 1.000000 1.000000 0.0000000 age 23.00000 22.00000 27.00000 18.00000 heigh 64.00000 66.00000 73.00000 58.00000 weigh 139.0000 112.0000 251.0000 86.00000 iq 101.0000 113.0000 129.0000 70.00000 gpa 3.050000 2.910000 3.790000 1.850000 var. std err of mean skewness coef. of var. sex 0.2088243e-01 -0.4522899e-01 97.84924 age 0.1160092 -0.3795715e-01 12.26888 heigh 0.1330046 0.4152664 4.981309 weigh 1.382710 0.5287957 23.29064 iq 0.7284885 -0.9540812e-01 17.29185 gpa 0.2106721e-01 -0.2985082 16.89175 statpack v4 PAGE 47 command: facto --------------- purpose: calculate factor analysis reference: "scientific subroutine package". description: the "facto" command allows the user to calculate a factor analysis for selected variables. the user will first be instructed to enter the options separated by commas (if no options are necessary type a ). possible options are: "const"--specify constant to decide how many eigenvalues to retain "evect"--include eigenvectors in output "factm"--include factor matrix in output "varia"--include variances in output "commu"--include communalities in output "fscor"--include factor scores in output "sfscr"--save factor scores "all"----include all above options if the "const" option has been specified, the user will first be asked to supply the constant value for retaining eigenvalues. unless the "const" option is specified, a constant value of 1.0 is assumed. when instructed the user should enter the variables, separated by commas for which the factor analysis is to be calculated. up to 40 variables may be entered using either variable names (if names have been defined) or variable numbers. ranges of variables may be indicated by typing the extremes of the range separated by a "-". one or more "*" may be used when listing the variables to be analyzed. one at a time each variable not yet specified in the analysis will be substituted for every "*". those cases where the same variable would be listed twice in the same analysis will be eliminated, as will be those cases that except for a switch in the order of the variables, duplicate an analysis already performed. statpack v4 PAGE 48 example: which command? facto list the options separated by commas help possible options: "evect"-print eigen vectors "factm"-print factor matrix "const"-specify constant to decide how many eigenvalues to retain "varia"-print variances "commu"-print communalities "fscor"-print factor scores "sfscr"-save factor scores "all" -all above options if no options are desired type a carriage return list the options separated by commas all what constant value would you like? 1.0 type in the variables, separated by commas 1-9 ***** factor analysis ***** variables: 1 2 3 4 5 6 7 8 9 eigen values 2.949910 1.643716 1.555180 1.065827 cumulative percentage of eigenvalues 0.3277678 0.5104030 0.6832007 0.8016259 eigen vectors vector 1 0.1643755 0.3483587 0.2879729 0.4966078 -0.1680629 -0.3292195 0.3993545 0.1287477e-01 0.4751829 vector 2 0.3483667 0.6551087e-01 -0.4464720 -0.1189327 0.6121037 -0.2642835 0.3886011 -0.2484407 -0.6013648e-01 vector 3 -0.2990021 -0.4682548 -0.2353323 0.1737775 0.1446729 -0.4354536 0.1880096e-01 0.6158744 0.1247019 vector 4 0.5444128 0.1690932 0.3828838 0.4162494e-01 0.3053685 -0.1616322 -0.4341069 0.4028344 statpack v4 PAGE 49 -0.2378870 factor matrix ( 4 factors) variable: 1 0.2823199 0.4466322 -0.3728760 0.5620458 variable: 2 0.5983167 0.8398985e-01 -0.5839458 0.1745700 variable: 3 0.4946021 -0.5724106 -0.2934754 0.3952851 variable: 4 0.8529389 -0.1524807 0.2167124 0.4297313e-01 variable: 5 -0.2886532 0.7847629 0.1804170 0.3152591 variable: 6 -0.5654445 -0.3388313 -0.5430404 -0.1668673 variable: 7 0.5859035 0.4982158 0.2344608e-01 -0.4481672 variable: 8 0.2211280e-01 -0.3185196 0.7680375 0.4158818 variable: 9 0.8161411 -0.7709947e-01 0.1555118 -0.2455919 iteration variances cycle 0 0.211289 1 0.336137 2 0.397023 3 0.403007 4 0.405181 5 0.405534 6 0.405587 7 0.405595 8 0.405596 9 0.405596 10 0.405596 11 0.405596 12 0.405596 statpack v4 PAGE 50 rotated factor matrix ( 4 factors) variable: 1 0.5498048e-01 0.7184287e-01 -0.5578176e-01 0.8501882 variable: 2 0.2932897 -0.3965333 -0.3558099 0.6055122 variable: 3 0.5113546e-01 -0.8249465 0.1506893 0.3298538 variable: 4 0.7404132 -0.4140190 0.2458024 0.1397243 variable: 5 -0.9091001e-01 0.8066388 0.1352510 0.3922847 variable: 6 -0.6828682 -0.2158005 -0.4498387 -0.2050298 variable: 7 0.8699805 0.1829980 -0.3491893 0.8830109e-01 variable: 8 0.3602174e-01 -0.5499635e-01 0.9137716 -0.1596276 variable: 9 0.8053224 -0.3275969 0.9939831e-02 check on communalities variable original final difference 1 0.73412 0.73412 0.00000 2 0.73650 0.73650 0.00000 3 0.81466 0.81466 0.00000 4 0.79957 0.79957 0.00000 5 0.83111 0.83111 0.00000 6 0.75727 0.75727 0.00000 7 0.92009 0.92008 0.00000 8 0.86478 0.86478 0.00000 9 0.75653 0.75653 0.00000 statpack v4 PAGE 51 factor scores 1 -1.490958 3.832233 -1.067173 -2.106546 2 1.198959 -0.6593465 -0.9128224 2.019913 3 1.424578 -1.453218 1.731582 0.6497848 4 4.805257 -1.572919 2.514179 -0.1405323 5 -5.638395 1.624943 1.808101 -2.416741 6 -3.724880 -1.390020 -1.040081 0.2053468e-01 7 -1.297509 3.529188 -0.6237091e-01 -2.239755 8 1.968393 -0.5822640 -0.5225442 3.182307 9 2.351696 -1.844730 -1.694724 1.499151 10 4.951994 -1.075510 2.141836 0.7312377 11 -4.471908 1.953006 2.304640 -1.182660 12 -3.467720 -1.791392 -0.8820030 -0.8098293 13 1.675869 -1.758742 -1.218959 0.6906289 14 0.5019671 -0.3294900 0.1332481 0.9855452 15 0.3846761 -0.5373469 -0.1268275e-01 0.6160892 16 1.381930 0.6014928 1.045720 1.713483 17 -0.5642744 3.375003 0.5186787 1.977829 18 -0.7676928 2.645897 -1.666019 -0.1859952 19 -0.9984410 1.030133 -2.250437 0.2990398 20 0.1735145 -0.7968859 0.1898848 -1.160393 21 0.6479561 -2.362979 1.079114 -2.574836 22 1.183074 -1.566329 1.541667 -0.5589452 23 -0.2280861 -0.8707238 -0.2156699 -1.009310 statpack v4 PAGE 52 command: fetch --------------- purpose: enter data which is stored on disk. limitation: will not input binary files. description: "fetch" allows the user to read data from the disk according to a standard format (separated by commas) or a user specified format. to specify his own format, the user must give a "form" command prior to the "fetch". in specifying the disk file to be used for input, the name and extension must be typed in separated by a period. by adding another user's project- programmer number enclosed in brackets, the data will be read from that area assuming the protection is correct. example: which command? fetch what is the filename and extension? file.dat[420,420] how many input variables? 2 statpack v4 PAGE 53 command: fini -------------- purpose: terminate execution of stat pack. description: the "fini" command allows the user to terminate execution of stat pack. once the command has been given, no other responses are necessary. output that was assigned to the line printer will be entered into the print queue for printing. the user will also be informed of the connect time and cpu time. note: the "fini" command must be used to ensure printing of results in instances where the output was assigned to the line printer. example: which command? fini cpu time: 4:22.68 elapsed time: 32:49.12 no execution errors detected exit statpack v4 PAGE 54 command: form -------------- purpose: specify input format. limitation: no fixed point or alphanumeric formats. description: when requested, the user enters a floating point format enclosed in parentheses. the total length of the format including the parentheses may be up to 480 characters. more than 1 line may be used to enter the format. blanks within lines will be removed. a format of (20f) is assumed at the beginning of each stp run, but a "form" command replaces it with the user specified format. example: which command? form enter your f-type data input format enclosed in parentheses (2x,3f1.0,1x,2f2.0,1x,f3.0,3x,f2.0) statpack v4 PAGE 55 command: freq -------------- purpose: produce frequency tables reference: "basic statistical methods", downe and heath, pages 16-19. description: the "freq" command is used to produce frequency of occurrence tables for one or more variables. the user will first be asked if he desires percentages, to which the response must be a "yes" or "no". next the user will be instructed to list the variables separated by commas for which frequencies are to be tabulated. up to 40 variables may be entered using either variable names (if names have been defined) or variable numbers. ranges of variables may be specified by typing the extremes of the range separated by a "-". where frequencies are to be tabulated for all variables, a "*" may be substituted for variable names and numbers. the tabled results will be labeled, and size of table adjusted to utilize space available for output. note: positive and negative numbers as well as multiple digit numbers may be processed with this command. example: which command? freq do you also want percentages (yes or no)? yes which variables? age,sex var. frequency and percentages ----- -------------------------------------------------------- age value 18.0 19.0 20.0 21.0 22.0 freq 45 49 58 64 66 % 7.8% 8.5% 10.1% 11.1% 11.5% value 23.0 24.0 25.0 26.0 27.0 freq 52 64 64 54 59 % 9.0% 11.1% 11.1% 9.4% 10.3% sex value .000 1.00 freq 281 294 % 48.9% 51.1% statpack v4 PAGE 56 command: help -------------- purpose: answer questions, supply alternatives. description: the "help" command is used when the response to a question is not obvious. it will supply the user with an explanation of what is necessary, the options available, or a list of commands. once the explanation or information has been supplied, the question will be restated, allowing the user to continue. examples: which command? help commands are broken into 6 groups: "dc" - data control "es" - elementary statistics "gr" - graphs "ia" - item analysis "as" - advanced statistics "pc" - program control "al" - complete command code list which set (type in the 2 character code)? dc commands available "data" - data input by tty "fetch" - read data from disk "form" - enter special input format "manip" - manipulate data in core (includes appending) "trans" - data transformations "store" - store data on disk "print" - print selected variables on line printer "type" - type out selected variables on tty "acbnk" - access a stored data bank "mta/i" - read data from mag tape which command? fetch what is the file name and extension? help the fetch command is used to read data from the disk. both the file name and extension must be specified. in order to read from another area the project, programmer number must be inserted in brackets directly adjoining the name and extension. statpack v4 PAGE 57 command: hist -------------- purpose: create histograms reference: "basic statistical methods", downe and heath, pages 25-27. description: the "hist" command allows the user to construct one or more histograms. when instructed, the user enters the variables separated by commas for which the histograms are to be created. up to 20 variables may be entered using either the variable names (if names have been defined) or variable numbers. ranges of variables may be indicated by typing the extremes of the range separated by a "-". where histograms are to be calculated for all variables, a "*" may be used in place of variable names and numbers. scaling will be automatically done with the number of divisions determined by the space available for output. the range of values included in each division will be listed in the output, as well as the frequency and percentage of observations falling into each division. example: which command? hist which variables? weight,height statpack v4 PAGE 58 *** histogram for variable: weigh ***** 40.00 + i i i i 30.00 + i ixxxxxi i ixxxxxixxxxxi i ixxxxxixxxxxi i ixxxxxixxxxxi 20.00 + ixxxxxixxxxxi i ixxxxxixxxxxixxxxxi i ixxxxxixxxxxixxxxxi i ixxxxxixxxxxixxxxxi i ixxxxxixxxxxixxxxxixxxxxi 10.00 + ixxxxxixxxxxixxxxxixxxxxi i ixxxxxixxxxxixxxxxixxxxxixxxxxi i ixxxxxixxxxxixxxxxixxxxxixxxxxi i ixxxxxixxxxxixxxxxixxxxxixxxxxixxxxxi i ixxxxxixxxxxixxxxxixxxxxixxxxxixxxxxi --+-----+-----+-----+-----+-----+-----+-----+ ^ 103 ^ 163 ^ 154 ^ 85 ^ 50 ^ 19 ^ 1 ^ ^ ^ ^ ^ ^ ^ ^ ^ ^ 111. ^ 161. ^ 211. ^ 261. 86.0 136. 186. 236. ***** histogram for variable: heigh ***** 40.00 + i i i i 30.00 + i i i i ixxxxxi 20.00 + ixxxxxixxxxxi i ixxxxxixxxxxixxxxxixxxxxi i ixxxxxixxxxxixxxxxixxxxxi i ixxxxxixxxxxixxxxxixxxxxi i ixxxxxixxxxxixxxxxixxxxxi 10.00 + ixxxxxixxxxxixxxxxixxxxxi i ixxxxxixxxxxixxxxxixxxxxixxxxxi i ixxxxxixxxxxixxxxxixxxxxixxxxxixxxxxi i ixxxxxixxxxxixxxxxixxxxxixxxxxixxxxxixxxxxi i ixxxxxixxxxxixxxxxixxxxxixxxxxixxxxxixxxxxixxxxxi --+-----+-----+-----+-----+-----+-----+-----+-----+ ^ 47 ^ 98 ^ 120 ^ 132 ^ 103 ^ 40 ^ 23 ^ 12 ^ ^ ^ ^ ^ ^ ^ ^ ^ ^ ^ 60.0 ^ 64.0 ^ 68.0 ^ 72.0 ^ 58.0 62.0 66.0 70.0 74.0 statpack v4 PAGE 59 command: info -------------- purpose: give the user a general program description. description: the "info" command allows the new user to obtain a brief description of the program while sitting at the terminal. once the command has been given, no other responses are necessary. the text will simply be typed out. example: which command? info stat pack is an integrated statistical package, written for terminal use. it allows the user to issue simple commands for data analysis. the program is in conversational mode and will prompt the user for desired information. in most instances when questions of procedure arise the user may request further information, by simply typing "help". standard form of output is terminal, but output may easily be channeled to the printer. input is readily accepted from terminal or disk. input consists of observations, each containing a value for all of the variables. each observation must begin a new line. the data may be input in either of two ways: 1) one observation per line with values separated by commas; or 2) according to your own input format which is entered using the command "form". after the last observation enter a ^z (cntrl z). to see the command list type "help" after "which command?" and "al" for the 2 character code. a restriction on data input is: 20 numbers maximum per line under standard format. if a line requires more than 72 columns use your own input format. statpack v4 PAGE 60 command: kendl --------------- purpose: produce a kendall tau correlation matrix. reference: "non-parametric statistics", siegel, pages 213-219. description: the "kendl" command allows the user to calculate and display kendall tau correlations between all variables. once the "kendl" command is given no other responses are necessary from the user. output is in the form of a well labeled matrix, with its size adjusting to the space available. example: which command? kendl ***** kendall tau correlation matrix ***** iq 1.0000 test1 0.0091 1.0000 test2 0.0230 0.0981 1.0000 test3 0.0163 0.7648 0.3377 1.0000 test4 0.7208 0.2999 0.0597 0.2834 1.0000 iq test1 test2 test3 test4 statpack v4 PAGE 61 command: kolm ---------------- purpose: calculate one or two sample kolmogorov-smirnov tests. reference: "statistical methods", b. h. lindgren, pages 329-335. description: the "kolm" command allows user to calculate one or two sample kolmogorov-smirnov tests. the user will first be instructed to enter the options desired separated by commas. possible options are: *** one sample options *** norml--test the variables to be specified against a normal distribution. (if no options are specified this will be the default). expon--test the variables to be specified against an exponential distribution. cauch--test the variables to be specified against a cauchy distribution. unifm--test the variables to be specified against an uniform distribution. total--test the variables to be specified against a normal, cauchy, uniform, and exponential distributions. suppl--normally the parameters calculated from the sample will be used to specify the distribution being tested, however, the suppl option allows the user to enter his own parameters for the distributions. *** two sample options *** 2samp--indicates test will be a two sample kolmogorov-smirnov test. break--rather than having the two samples coming from two variables, select the two samples from a single variable based on the value of another variable (breakdown variable). this option is available only if "2samp" has been used. discr--ranges calculated automatically with a separate range created for each unique value. if this option is not used it will be necessary for the user to enter the ranges. if statpack v4 PAGE 62 more than 20 unique values exist for the breakdown variable, it will also be necessary for the user to enter ranges. this option only available if "break" is used. range--list ranges calculated. this option only available if "discr" is used. for the one sample test the user will be instructed to enter the variables to be tested against the distributions specified. up to 20 variables may be entered separated by commas. variable numbers or variable names (if names have been defined) may be used to indicate the variables. ranges of variables may be specified by entering the extremes of the range separated by a "-". if all variables are to be tested the user may use a "*". no other responses are necessary unless the suppl option was specified. if "suppl" was used, the user must supply the parameters for the various distributions when requested. for the two sample test the user will be instructed to enter the variables separated by commas. up to 20 variable numbers or variable names (if names have been defined) may be entered. ranges of variables may be specified by typing the extremes of the range separated by a "-". if all variables are to be used an "*" may be entered. if the break option has not been used, no other information need be entered. if the break option has been used, it will be necessary for the user to enter the breakdown variable. either the variable number or variable name (if names have been defined) may be used. if the option "discr" has not been specified the user must enter the ranges for the breakdown variable. up to 20 ranges for the breakdown variable are entered, one range per line. each range is comprised of a minimum for the range, a comma, and a maximum. when the last range has been entered, type a control z (^z) or carriage return. statpack v4 PAGE 63 examples: which command? kolm enter options separated by commas total enter variables to be tested separated by commas 2,3 ***** kolmogorov-smirnov test ***** var. distribution tested against d1 prob grade normal mean= 5.28571 stdev= 1.12646 .1941 0.143* exponential mean= 5.286 stdev= 1.126 .2688 0.013* cauchy 1st quart.= 4.250 median= 5.000 .2523 0.023* uniform from 3.000000 to 7.000000 .2429 0.032* iq normal mean= 100.000 stdev= 30.0000 .6899e-01 0.996* exponential mean= 100.0 stdev= 30.00 .1587 0.341* cauchy 1st quart.= 79.75 median= 96.71 .1060 0.826* uniform from 42.84538 to 172.0905 .1981 0.128* the hypothesis that the sample is from the specified distribution can be rejected with the indicated probability (prob) of being incorrect. *the probability may not be correct for the sample sizes being used. for more accurate probabilities check the tables in non-parametric statistics by siegel. which command? kolm enter options separated by commas 2samp enter variables separated by commas * statpack v4 PAGE 64 ***** kolmogorov-smirnov 2 sample test ***** var. size var. size d2 prob 1 60 2 60 0.2333333 0.076* 1 60 3 60 0.4833333 0.000* 2 60 3 60 0.4666667 0.000* the hypothesis that the 2 samples are drawn from the same population can be rejected with the indicated probability (prob) of being incorrect. *the probability may not be correct for the sample sizes being used. for more accurate probabilities check the tables in non-parametric statistics by siegel. which command? kolm enter options separated by commas break,discr,range break, discr, and range are only available on 2 sample tests enter options separated by commas 2samp,break,discr,range enter variables to be analyzed, separated by commas 2,3 which is the breakdown variable? 1 1.000 , 1.000 2.000 , 2.000 ***** kolmogorov-smirnov 2 sample test ***** var. smp a size smp b size d2 prob 2 1 29 2 31 0.1434928 0.917* 3 1 29 2 31 0.1768632 0.737* the hypothesis that the 2 samples are drawn from the same population can be rejected with the indicated probability (prob) of being incorrect. *the probability may not be correct for the sample sizes being used. for more accurate probabilities check the tables in non-parametric statistics by siegel. statpack v4 PAGE 65 which command? kolm enter options separated by commas break,2samp enter variables to be analyzed, separated by commas 2,3 which is the breakdown variable? 1 enter ranges for breakdown variable 1 ? 1,1 ? 2,2 ? ***** kolmogorov-smirnov 2 sample test ***** var. smp a size smp b size d2 prob 2 1 29 2 31 0.1434928 0.917* 3 1 29 2 31 0.1768632 0.737* the hypothesis that the 2 samples are drawn from the same population can be rejected with the indicated probability (prob) of being incorrect. *the probability may not be correct for the sample sizes being used. for more accurate probabilities check the tables in non-parametric statistics by siegel. statpack v4 PAGE 66 command: mabnk --------------- purpose: create a bank from data in stp. description: the "mabnk" command allows users to make a bank file from data located in stp. when the name for the bank is requested, the user should type in a name of at most 6 characters; no extension is necessary as a ".bnk" will be supplied. all variables in stp will be put into the bank in the same order as they occur in stp. if variable names are not assigned in stp, generated names of "v1", "v2", "v3", ..., will be given to the variables in the bank. a standard protection code of <155> will be assigned to the bank unless otherwise specified by the user. banks are stored as binary random access files to increase recovery speed, and eliminate formatting problems. do not attempt to print bank files; output will not be meaningful, and large amounts of line printer paper will be wasted. example: which command? mabnk bank name? john what protection? 177 statpack v4 PAGE 67 command: make -------------- purpose: document output with one or more pages of user submitted information. description: the "make" command allows the user to insert one or more pages of documentation into program generated output. after the make command is issued, the user is instructed to enter his page or pages of documentation. when finished, the user types a , an altmode, and another . the information submitted by the user is entered into the output only once, at that point in the output where the "make" command was requested. the text is transferred to the output line by line, thus corrections to previous lines are not possible. if corrections are to be made to the line currently being typed in, rubouts may be used. each rubout used erases the previous character. lines may be up to 120 characters long. a disk file may also be used as the text to be inserted into the output. to specify a disk file the user types an "@" and the name of the file with the extension. the file must reside in the area from which stat pack is being run. examples: which command? make *** documentation *** this output is from the stat pack program run on 4-12-74. input is from the file oberl.dat in area 220,220. its variables are defined as follows: var var num name description --- ---- ----------- 1 sex sex of respondant 1-female 2-male 2 age age in years (nearest birthday) 3 gpa grade point average (4.0=a) $ which command? make @sampl.doc statpack v4 PAGE 68 command: manip --------------- purpose: correct mistakes in data, make allowances for missing data, add variables or observations, and modify or discard observations which do not meet certain criteria. description: "manip" is a command allowing the user to issue instructions one at a time, to delete, type, modify, or add to data which has been entered in statpack. each instruction has the following three parts: a. what operation is to be performed each instruction must have as the first character a code indicating what the instruction does. "a"-add to the data "d"-delete data "e"-return to "which command?" "r"-replace data with new values "t"-type data on terminal b. what portion of the data is to be acted upon by the operation this portion of the "manip" instruction indicates which section of the data is to be acted upon. the observation number and variable number or name are used for such reference. to indicate a particular observation an "o" is followed by the observation number. to define a variable a "v" is followed by the variable number or if names are defined for the variables, the name enclosed in parentheses. ranges of variables or observations may be indicated by following the "v" or "o" with the smallest number in the range, a "-" (dash), and finally with the largest number in the range. when only those values which meet certain criteria are to be acted upon, a search is used. the coding for a search consists of an "s" followed by a conditional code and a numerical value used as a reference for the conditional code. these codes are: ">" or "g"-greater than "<" or "l"-less than "=" or "e"-equal to the condition code is modified by the value which follows it, indicating the value to be searched for and the relationship that must be satisfied in order to act upon the data. c. what extra information is desired or previously defined during execution of instruction strings, a report is written on the terminal containing variable names or numbers, observation numbers, and values at these points. if the report is unnecessary or unwanted, a "w" will cause it to be suppressed. statpack v4 PAGE 69 normally, when an instruction has been issued to replace or add data, the values to be inserted are supplied by the user, one at a time in response to a single question mark. a constant value to be used for that instruction may be supplied (eliminating the need to type in data upon cue), by inserting a "c" followed by the numeric value to be used as the constant. two special constants are also available: the mean of the variable, and the mean of the variable calculated by ignoring all occurrences of a particular value. if the mean of the variable is to be used as the constant, replace the "c" and its associated value by an "m". if the constant to be used is the mean calculated by ignoring a particular value, as with missing data, replace the "m" with an "l" followed by the value to be ignored during calculation of the mean. when typing an instruction to "manip" there may be no spaces, and the first character must be the code indicating what is to be done. no particular order must be maintained beyond the first character. a double question mark indicates an instruction should be inserted. a single question mark is used to indicate a numeric value is to be inserted for data. examples:(assume original data to be) variable variable variable variable (1) (2) (3) (4) observation 1 1 3 5 7 observation 2 2 9 4 3 observation 3 6 8 4 3 observation 4 2 1 7 9 observation 5 5 8 6 8 observation 6 1 1 3 2 observation 7 4 7 3 1 observation 8 6 2 3 5 which command? manip ?? to1 type the values for all variables in observation 1 var. obs value 1 1 1.00 2 1 3.00 3 1 5.00 4 1 7.00 statpack v4 PAGE 70 ?? to1w type the values for all variables in observation 1 leaving off the variable and observation identification 1.00 3.00 5.00 7.00 ?? tv2w type the values for all observations in variable: 2 leaving off the variable and observation identification 3.00 9.00 8.00 1.00 8.00 1.00 7.00 2.00 ?? to2-3v2-3 type the values of observa- tions 2 and 3, for variables 2 and 3 var. obs value 2 2 9.00 2 3 8.00 3 2 4.00 3 3 4.00 ?? tse3 type all the values equal to 3 identified by variable and observation numbers var. obs value 2 1 3.00 3 6 3.00 3 7 3.00 3 8 3.00 4 2 3.00 4 3 3.00 ?? tv2se3 type all those cases where variable: 2 is equal to 3 var. obs value 2 1 3.00 statpack v4 PAGE 71 ?? ro4v3 replace the value (7) in observation 4 of variable: 3 with the new value (8) entered from the terminal in response to the question mark var. obs value new value 3 4 7.00 ?8 ?? ro4v3c7 replace the value (8) in observation 4 of variable: 3 with the constant value 7 var. obs value new value 3 4 8.00 7.00 ?? rse3v3c8 replace those observations in variable 3 having the value (3) with the constant value (8) var. obs value new value 3 6 3.00 8.00 3 7 3.00 8.00 3 8 3.00 8.00 ?? rv3o6 replace observation 6 of variable: 3 with the new value (3) entered from the terminal in response to the question mark var. obs value new value 3 6 8.00 ?3 ?? rv3o7-8c3 replace the value (8) in observations 7 and 8 of variable 3 with the constant value (3.0) var. obs value new value 3 7 8.00 3.00 statpack v4 PAGE 72 ?? ao9 create a new observation (9), with the values 3,5,7, and 4 (entered from terminal) being used for variables 1-4 var. obs new value 1 9 ?3 2 9 ?5 3 9 ?7 4 9 ?4 ?? av5c3.0 create a new variable (5) where all observations are automatically set equal to the constant value 3 var. obs new value 5 1 ? 3.00 5 2 ? 3.00 5 3 ? 3.00 5 4 ? 3.00 5 5 ? 3.00 5 6 ? 3.00 5 7 ? 3.00 5 8 ? 3.00 5 9 ? 3.00 ?? dv5 delete variable 5 ?? ro9m replace observation 9 with the mean of each variable. thus variable 1, observation 9 will be equal to the mean of variable 1; variable 2, observation 9 will be equal to the mean of variable 2, etc. var. obs value new value 1 9 3.00 3.33 2 9 5.00 4.89 3 9 7.00 4.67 4 9 4.00 4.67 ?? ro9 replace the values for all variables in observation 9 with values entered on the terminal in in response to question marks var. obs value new value 1 9 3.33 ?3 2 9 4.89 ?5 3 9 4.67 ?7 4 9 4.67 ?4 statpack v4 PAGE 73 ?? ro9l3 replace observation 9 of all variables with the mean of each variable calculated by discarding all the observations having a value 3 for that variable var. obs value new value 1 9 3.00 3.37 2 9 5.00 5.13 3 9 7.00 5.50 4 9 4.00 5.14 ?? do9 delete observation 9 ?? t type the entire set of data var. obs value 1 1 1.00 1 2 2.00 1 3 6.00 1 4 2.00 1 5 5.00 1 6 1.00 1 7 4.00 1 8 6.00 2 1 3.00 2 2 9.00 2 3 8.00 2 4 1.00 2 5 8.00 2 6 1.00 2 7 7.00 2 8 2.00 3 1 5.00 3 2 4.00 3 3 4.00 3 4 7.00 3 5 6.00 3 6 3.00 3 7 3.00 3 8 3.00 4 1 7.00 4 2 3.00 4 3 3.00 4 4 9.00 4 5 8.00 4 6 2.00 4 7 1.00 4 8 5.00 ?? e exit statpack v4 PAGE 74 command: mann -------------- purpose: calculate mann-whitney u reference: "basic statistical methods", downe and heath, pages 213, 214. "non-parametric statistics", siegel, pages 116-127. description: the "mann" command allows the user to calculate mann-whitney u. the user will first be instructed to list the options desired, separated by commas. if no options are desired type a . possible options are: "break"--select samples from one variable based on the value of a second variable. for each observation, the value of the second variable (breakdown variable) will be used to determine in which sample the variable being analyzed belongs. this is accomplished by determining which of a series of ranges the value of the breakdown variable fits into, and then moving the value of the analysis variable to the corresponding sample. (if this option is not used, mann-whitney u's will be calculated between variables.) note: the following options are to be used only if "break" has been used. "discr"--automatic breakdown. instead of the user entering ranges, a separate range will be created automatically for each value in the breakdown variable. "auto"--automatic breakdown. this option is the same as the "discr" option. do not enter "auto" with the other options, it should be used only when asked to enter the ranges. the "discr" and "auto" options are equivalent; the only difference is at which point in the program they are entered. note: the following option is available only if automatic breakdown is to be used. "range"--list the ranges to be used for the automatic breakdown. if the "break" option has not been specified, mann-whitney u will be calculated between all possible pairs of variables. no other user responses will be necessary. if the "break" option has been used, it will be necessary for the user to supply the following information: statpack v4 PAGE 75 (1) the variables for which mann-whitney u are to be calculated (up to 20). the samples for each set of mann-whitney u will be selected from a single variable. variables may be listed using either variable names (if names have been defined) or variable numbers. ranges of variables may be specified by listing the extremes of the range separated by a "-". where mann-whitney u's are to calculated for all variables, a "*" may be used instead of variable names or numbers. (2) the variable to be used for the breakdowns. only one variable may be entered, specified by either its variable name (if the name has been defined) or variable number. all variables listed for analysis will be processed using the same breakdown variable. (3) ranges for the breakdown variable. if the "discr" option has been used, this information will be automatically calculated, and need not be supplied by the user. if the "discr" option has not been used, the user may still request the ranges be automatically calculated by responding with "auto". to specify ranges, the user types the extremes of range, smaller first, separated by a comma. only one range may be entered per line. up to 50 ranges may be specified. after the last range has been entered, the user types a ^z(control z). example: which command? mann list options separated by commas ***** mann-whitney u-test ***** var. vs var. mean standard deviation z n1 n2 u1 u2 ---------------------------------------------------------------- iq test1 156240.5 5398.042 28.90354 559 559 312263.0 218.0000 iq test2 156240.5 5398.042 28.88862 559 559 312182.5 298.5000 test1 test2 156240.5 5398.042 -6.136114 559 559 123117.5 189363.5 statpack v4 PAGE 76 command: mta/i --------------- purpose: read data stored on magnetic tape, with the ability to select variables, and subset data (leave out observations which do not meet user specified criteria). limitation: data must be in ascii mode on magnetic tape, line-blocked and recorded at 556 bpi. (these are normal w.m.u. magnetic tape standards.) tape must be located at computer center or given to operator prior to run. description: the "mta/i" command is used to read data located on magnetic tapes. if the format of the tape is other than the standard format (20f) the "form" command should be used prior to the "mta/i" command. the user will first be instructed to type in some identification for the tape. a single line of 26 characters should be typed in, containing tape i.d. no.(if available), name of user, or other identification. this message is sent to the operator, along with the project-programmer number of the user. the operator has a choice of five responses; they are: no drives are available, tape cannot be located, the user does not have one of the project-programmer numbers for which the tape is reserved, more information needed, or the tape has been mounted. if a magnetic tape drive is free and the user may access the requested magnetic tape, the magnetic tape will be mounted on the free drive and the user informed of the drive number. if the tape has not been mounted, check the following list to determine proper course of action: operator's reply action to be taken ---------------- ------------------ no drives available wait and request tape later tape cannot be located 1. check and make sure right i.d. number was used 2. make sure tape is at computer center 3. contact operator to determine problem users project-programmer the owner of the tape must number does not appear on the send a signed note to the list of numbers which may to the computer center access the tape containing any additions or changes of proj-prog numbers which may access the tape. statpack v4 PAGE 77 operator needs more type in another line of up to information 30 characters of i.d. the user will then be asked which position on the tape the file he wishes to access occupies. if the file is the only one on the tape or was the first one written on the tape, then it occupies position number 1. if it was the second one written on the tape, then it occupies position number 2, etc. when the user has answered this question, the magtape will advance to the proper file. the user will then be asked how many variables it will be necessary to look at. this includes variables which may only be used as qualifiers. next, when instructed, the user types in the qualifiers (50 maximum), one per line with no spaces. each qualifier checks one variable to make certain it contains a specified value or range of values. if the qualifier is not satisfied the observation being scrutinized is discarded, and the next observation considered. each qualifier is composed of three parts: the number of the variable to be checked, the relationship which must be satisfied if the observation is to be accepted, and the value which the variable is compared against. the relationships possible are: ,eq, - equal ,ne, - not equal ,lt, - less than ,gt, - greater than ,le, - less than or equal to ,ge, - greater than or equal to after the last qualifier has been typed, a , ^z, or "stop" may be typed. the user is then instructed to list the numbers of the variables which are to be used as data, separated by commas. the first variable listed becomes variable number 1 in the data set, the second variable listed becomes variable number 2, etc. when either the entire file has been considered or the data set has been filled, the user will be informed of the number of observations in the data set, and the number of records from which the data was selected. when finished, before logging off the computer, indicate to the operator to remove the magnetic tape from the drive. example: which command? mta/i please give some identification for the tape? mag tape #1234 tape has been mounted on mta0 write protected. be sure to ask to have the tape dismounted when done what position does the file occupy on the tape? 1 statpack v4 PAGE 78 how many variables? 4 list qualifiers 1 per line ? 2,le,9 ? 3,ge,0 ? ^z list the variables to be kept, separated by commas 1,2,4 data set consists of 36 observations as selected from a sample of 36 statpack v4 PAGE 79 command: name -------------- purpose: assign names to variables limitation: maximum of five characters per name description: the "name" command allows the user to assign names to variables. one at a time, each variable number will be typed out followed by a question mark. in response, the user may type in the name he has selected for that variable, subject to the following limitations: (1) maximum of five characters (2) first character must be alphanumeric (3) ";", ",", "-", or blanks must not be present in the name (4) "all", "stop", "help", "empty", and "obs" are not legal names (5) two variables must not be given the same name if it is not necessary to name a variable, or if the variable has been previously given a name and it does not need to be changed, the user may type a . names will be kept only until the end of the run or until a new set of data is read. the "store" command does not store names with the data, if the names are necessary, they will have to be input each time the data is fetched. the names are primarily used to label output, but they may be used whenever it is necessary to specify a variable. example: which command? name var 1? iq var 2? test1 var 3? test2 var 4? test3 var 5? test4 statpack v4 PAGE 80 command: 1wayr --------------- purpose: calculate one way analysis of variance with repeated measures. reference: "statistical principles in experimental design", winer, pages 105-113. description: the "1wayr" command allows the user to calculate a one way analysis of variance with repeated measures. when instructed, the user lists the variables separated by commas for which he wishes to have an analysis of variance calculated. up to 50 variables may be entered, using either variable names (if names have been defined) or variable numbers. ranges of variables may be entered by typing the extremes of the range separated by a "-". one or more "*" may be used when listing the variables to be analyzed. one at a time each variable not yet specified in the analysis will be substituted for every "*". those cases where the same variable would be listed twice in the same analysis will be eliminated, as will be those cases which, except for a switch in the order of the variables, duplicate an analysis already performed. output will be labeled with variable names, if available; otherwise, variable numbers will be used. output size will be adjusted to fully utilize space available. example: which command? 1wayr which variables? test1,test2,test3,test4 ***** 1-way anova with repeated measures ***** tret. size mean std. dev. test1 559 41.75 21.73741 test2 559 49.68 18.73237 test3 559 47.88 12.27697 test4 559 64.81 19.69569 source sum of sq. d.f. mean sq. f prob between 403319.0 558 within 517612.4 1677 treat. 160901.6 3 .5363e+05 251.7 0.0000 resid. 356710.8 1674 213.1 total 920931.4 2235 statpack v4 PAGE 81 command: pcent --------------- purpose: calculate user specified percentiles reference: "basic statistics", downe and heath, pages 36,37. description: the "pcent" command allows the user to calculate selected percentiles for one or more variables. when prompted, the user lists the variables separated by commas for which the percentiles are to be calculated. up to 20 variables may be entered using either the variable names (if names have been defined) or variable numbers. ranges of variables may be indicated by typing the extremes of the range separated by a "-". where percentiles are to be calculated for all variables, a "*" must be substituted for variable names and numbers. the user will then be instructed to list the percentiles he wishes to have calculated separated by commas. up to 20 percentiles may be entered. if either the deciles (10th, 20th, 30th,...80th, 90th percentiles) or quartiles (25th, 50th, and 75th percentiles) are desired, they may be obtained by responding with "dec" for the deciles or "qtr" for the quartiles. examples: which command? pcent which variables? height,weight,iq,gpa type in percentiles you wish to have, separated by commas dec ***** percentiles ***** variables percentile heigh weigh iq gpa ---------- -------------------------------------------- 10.00 60.00 102.0 76.00 2.250 20.00 61.00 112.0 82.00 2.535 30.00 62.00 120.0 89.00 2.690 40.00 63.00 131.0 96.00 2.890 50.00 64.00 139.0 101.0 3.050 60.00 65.00 148.0 108.0 3.190 70.00 66.00 157.0 113.0 3.340 80.00 66.00 170.0 119.0 3.500 90.00 68.00 188.0 125.0 3.640 statpack v4 PAGE 82 which command? pcent which variables? height,iq,weight,gpa type in percentiles you wish to have, seperated by commas 5,10,15,20,25,50,75,80,90,95,99 ***** percentiles ***** variables percentile heigh iq weigh gpa ---------- ----------------------------------------------- 5.00 59.00 73.00 94.50 2.085 10.00 60.00 76.00 102.0 2.250 15.00 60.00 80.00 106.0 2.387 20.00 61.00 82.00 112.0 2.535 25.00 61.00 85.25 116.0 2.620 50.00 64.00 101.0 139.0 3.050 75.00 66.00 116.0 163.0 3.400 80.00 66.00 119.0 170.0 3.500 90.00 68.00 125.0 188.0 3.640 95.00 70.00 127.0 204.0 3.720 99.00 72.00 129.0 226.2 3.780 statpack v4 PAGE 83 command: pcorr --------------- purpose: calculate partial correlations reference: "an introduction to multivariate statistical analysis", t.w. anderson, pages 31-32, 86-87. description: the "pcorr" command allows the user to calculate a partial correlation matrix for specified variables. when instructed, the user enters the variables separated by commas, for which partial correlations are to be calculated. up to 20 variables may be entered, using either variable names (if names have been defined) or variable numbers. ranges of variables may be entered by listing the extremes of the range separated by a "-". one or more "*" may be used when listing the variables to be analyzed. one at a time each variable not yet specified in the analysis will be substituted for every "*". those cases where the same variable would be listed twice in the same analysis will be eliminated, as will be those cases that except for a switch in the order of the variables, duplicate an analysis already performed. output will be labeled with variable names, if available; otherwise, variable numbers will be used. output size will be adjusted to fully utilize space available. example: which command? pcorr which variables? gpa,iq,sex,age,weight,height ***** partial correlation matrix ***** iq 0.0139 sex 0.0001 -0.0090 age 0.0400 -0.0463 0.0480 weigh 0.0368 0.0674 0.3946 0.0380 heigh -0.0023 -0.0395 -0.0345 -0.0869 0.7753 gpa iq sex age weigh statpack v4 PAGE 84 command: plot -------------- purpose: produce bivariate scatter plot reference: "basic statistical methods", downe and heath, pages 79-82. description: the "plot" command allows the user to produce a bivariate (two variable) scatter plot. scatter plots may be produced for the following: (1) a single variable vs a single variable (2) a single variable vs all other variables (3) all variables vs all variables it will be necessary for the user to supply first the horizontal and then the vertical axes. either variables names (if names have been defined) or variable numbers may be used. where all variables are to be used a "*" may be substituted for variable names or numbers. the plot is automatically scaled in both the horizontal and vertical directions, and its size is adjusted to utilize space available. the digits 1 through 9 indicate the number of observations occupying a single point in the graph. letters (a-z) are used when more than 9 observations occupy the same location, starting with a to indicate 10 numbers, b to indicate 11, etc., and z to indicate 35. if more than 35 observations occupy a single point a "*" will be used. example: which command? plot which is the horizontal variable? height which is the vertical variable? weight statpack v4 PAGE 85 plot of variable heigh (horiz.) vs variable weigh (vert.) i---------+---------+---------+---------+ 251.0 + 1 i i 1 1 i 1 3 2 219.0 + 1 2 1 1 1 1 1 i 1 2 1 2 1 i 2 1 4 2 2 3 i 2 1 1 1 4 2 1 2 187.0 + 1 5 5 5 2 1 1 i 4 8 3 3 1 i 3 d a 3 4 1 1 i 1 6 3 9 7 3 155.0 + 2 4 6 c 6 e 4 1 3 i 1 2 1 7 9 f 5 4 1 i 1 7 7 f 7 8 9 2 1 i 4 9 9 9 d 4 6 1 123.0 +1 6 7 9 7 9 2 4 i1 9 c d 4 c 7 4 1 i a 4 3 9 7 2 1 i d 7 7 4 6 1 91.00 + a 8 5 3 i 1 2 i i 59.00 + i---------+---------+---------+---------+ 57.60 65.60 73.60 61.60 69.60 statpack v4 PAGE 86 command: print --------------- purpose: print selected variables on the line printer. description: the "print" command is used to obtain a copy of the data listed on the line printer. when asked for the variables to be printed, the user types the variables on one line separated by commas. variables may be entered using either variable names (if names have been defined) or variable numbers. ranges of variables may be specified by listing the extremes of the range separated by a "-". where all variables are to be printed, use a "*" instead of variable names or numbers. output is always to the line printer with multiple copies available by using the "copys" command prior to the "print" command. printouts may be picked up at the output window in the computer center, by asking for the printout and giving the users project-programmer number. the computer center is located on the third floor of rood hall. the "type" command is also available for copies of data in smaller quantities, via the terminal. example: which command? print which variables? sex,age,3,5-6 example output: var obs sex age 3 5 6 1 1.000000 23.00000 4.000000 9.000000 7.000000 2 1.000000 21.00000 6.000000 8.000000 9.000000 3 1.000000 25.00000 7.000000 9.000000 6.000000 4 2.000000 18.00000 6.000000 5.000000 3.000000 5 2.000000 18.00000 5.000000 6.000000 7.000000 6 2.000000 19.00000 7.000000 9.000000 6.000000 7 1.000000 16.00000 6.000000 7.000000 5.000000 8 2.000000 24.00000 5.000000 7.000000 8.000000 9 2.000000 21.00000 4.000000 7.000000 8.000000 10 2.000000 20.00000 3.000000 4.000000 2.000000 statpack v4 PAGE 87 command: prob -------------- purpose: calculate probabilities associated with t tests, f tests, and chi squares. description: the "prob" command allows the user to calculate probabilities associated with t tests, f tests, and chi squares. to indicate to the user that an instruction should be inserted, a "?" will be typed out. this will be the first reply to the "prob" command, and will appear after each probability calculated. instructions may be entered in either of two ways: (1) a code indicating the type of probability desired (the user will be prompted for additional information). the codes are: chi--chi square t----t test f----f test (2) the code and information are entered in one line (no prompting except for "?" is necessary here). the codes and information are entered in the following manner, with no spaces between any characters: chi square ---------- chi##,df the three character code "chi" followed by the value of the chi square (the chi square is substituted for the "##" in the above string). this is followed by a comma, and finally, the degrees of freedom (degrees of freedom substituted for "df".) t test ------ t##,df the single character code "t" followed by the value of the t score (the t score is substituted for the "##" in the above string). this is followed by a comma, and finally the degrees of freedom (degrees of freedom substituted for "df"). f tests ------- f##,ndf,ddf the single character code "f" followed by the value of the f score (f score substituted for the "##" in the above string). next a comma, and then the degrees of freedom in the numerator (degrees statpack v4 PAGE 88 of freedom in the numerator will replace the "ndf" in above string). finally, a comma followed by the degrees of freedom in the denominator (degrees of freedom in the denominator will replace the "ddf" in above line). included in the output will be a statement of the parameters supplied as well as the probabilities calculated. both the one-tailed and two-tailed probabilities will be calculated for the t tests. to return to "which command?" enter an "exit", , or ^z(control z). examples: which command? prob "?" indicates program is waiting for instruct. ? chi what is the value of the chi. sq.? 5.892 how many degrees of freedom? 13 the prob for a chi sq of 5.892 with 13 degrees of freedom is .95 ? chi5.892,13 the prob for a chi sq of 5.892 with 13 degrees of freedom is .95 ? chi5.892 how many degrees of freedom? 13 the prob for a chi sq of 5.892 with 13 degrees of freedom is .95 ? t what is the value of the t? 2.571 how many degrees of freedom? 5 the prob. for a t of 2.571 with 5 degrees of freedom is: one tailed 0.0250; two tailed 0.0500 ? t2.571 how many degrees of freedom? 5 the prob. for a t of 2.571 with 5 degrees of freedom is: one tailed 0.0250; two tailed 0.0500 ? t2.571,5 the prob. for a t of 2.571 with 5 degrees of freedom is: one tailed 0.0250; two tailed 0.0500 statpack v4 PAGE 89 ? f what is the value of the f? 27.34 how many degrees of freedom in the numerator? 9 how many degrees of freedom in the denominator? 3 prob for an f of 27.34 with 9 degrees of freedom in the numerator and 3 degrees of freedom in the denominator is 0.0100 ? f27.340 how many degrees of freedom in the numerator? 9 how many degrees of freedom in the denominator? 3 prob for an f of 27.34 with 9 degrees of freedom in the numerator and 3 degrees of freedom in the denominator is 0.0100 ? f27.34,9,3 prob for an f of 27.34 with 9 degrees of freedom in the numerator and 3 degrees of freedom in the denominator is 0.0100 ? ^z statpack v4 PAGE 90 command: ptbis --------------- purpose: calculate point biserial correlations reference: "basic statistical methods", downe and heath, pages 169-172 description: the "ptbis" command allows the user to calculate point biserial correlations. when requested, the user enters up to 20 variables separated by commas. variable numbers or variable names (if names have been defined) may be used. ranges of variables may be specified by typing the extremes of the range separated by a "-". the user will next be instructed to enter the dichotomous variable. either the variable number or variable name (if names have been defined) may be used. if more than 2 unique values exist, it will also be necessary to specify a breakpoint for the dichotomous variable. all values less than or equal to the breakpoint will be treated as one portion of dichotomy while all values greater than the breakpoint will be the other portion. when instructed the user enters a value for the breakpoint, or if the median is to be used as the breakpoint "median" may be specified. examples: which command? ptbis which variables? 2,3 which is the dichotomous variable? 1 **** point biserial correlation **** variable: rorw is the dichotomous variable the lower group size is 14 and the upper group size is 21 point-biserial mean of mean of standard correlation with variable low group high group deviation variable:rorw grade 5.0714 5.4286 1.1265 0.1553218 iq 93.671 104.22 30.000 0.1722583 statpack v4 PAGE 91 which command? ptbis which variables? 2 what is the breakpoint for variable: iq ? median **** point biserial correlation **** variable: iq is the dichotomous variable the breakpoint being used to split the variable is 96.70642 the lower group size is 18 and the upper group size is 17 point-biserial mean of mean of standard correlation with variable low group high group deviation variable:iq grade 5.5000 5.0588 1.1265 -0.1957447 which command? fini statpack v4 PAGE 92 command: regr -------------- purpose: produce multiple regressions reference: "statistical methods", snedecor and cochran, pages 381-418 description: the "regr" command allows the user to produce multiple regression on selected variables. when instructed, the user enters the option desired. only one option exists for the "regr" command. it is: "resid"--store residuals if this option is not to be used, type a . if the "resid" option has been specified the user will be asked to indicate under which variable the residuals are to be stored. the variable name (if the name already exists) or the variable number may be used in storing the residuals. once the residuals have been stored in the variable, the variable name will be changed to "resid". the user will be instructed to list the independent variables separated by commas. up to 19 variables may be listed by variable names (if names have been defined) or variable numbers. ranges of variables may be indicated by typing the extremes of the range separated by a "-". one or more "*" may be used when listing the variables. one at a time each variable not yet specified in the analysis will be substituted for every "*". those cases where the same variable would be listed twice in the same analysis will be eliminated, as will those cases which except for a change in the order of variables, duplicate an analysis already performed. finally, the user will be asked to enter the dependent variable. either the variable name (if names have been used) or the variable number may be used. if the user wishes to substitute in one at a time all those variables not specified as independent, he may respond with a "*". the "*" may be used both as the dependent variable, and as one or more independent variables in the same analysis. statpack v4 PAGE 93 example: which command? regr enter options separated by commas list the independent variables? sex,age,gpa which is the dependent variable? iq ***** multiple linear regression ***** sample size 575 dependent variable: iq independent variables: sex age gpa coefficient of determination 0.00336 multiple corr coeff. 0.05797 estimated constant term 105.10621 standard error of estimate 17.469706 analysis of variance for the regression source of variation df s. sq. m.s. f prob regression 3 587.599 195.866 .6418 0.5923 residuals 571 174264. 305.191 total 574 174851. regression s. e. of f-value corr.coef. var. coefficient reg. coef. df (1, 571) prob with iq sex 1.132208 1.459 .6020 0.4382 0.0318 age -0.2885458 .2626 1.207 0.2724 -0.0443 gpa 0.5975427 1.447 .1705 0.6798 0.0169 statpack v4 PAGE 94 command: sort -------------- purpose: allow user to sort data into ascending order description: data may be sorted into ascending order by use of the "sort" command. when instructed to enter sort keys, the user types in up to 20 variables separated by commas. variable names (if names have been given) or variable numbers may be used. ranges of variables may be specified by typing the extremes of the range separated by a "-". the sort fields should be listed from major to minor. when the sort has been completed, each observation will remain unaltered, only the order in which the observations occur will have been changed. the major sort key (first variable in the list) is used to determine which of two observations is first. if no decision can be made as in the case of a tie, the next variable in the list of sort keys is used. the sort proceeds in this manner always checking the next variable in the list, until it reaches the minor sort key (the last variable in the list). if no decision can yet be made, they are left in the same order as they occur. example: which command? sort list sort variables major to minor? 1-3 data sorted by variables: sex , age , weight statpack v4 PAGE 95 command: srank --------------- purpose: produce spearman rank-order correlations reference: "non-parametric statistics", siegel, pages 202-213 description: the "srank" command allows the user to calculate spearman rank-order correlations between all variables. after the command is given no other responses are necessary. example: which command? srank ***** spearman rank-order corr. matrix ***** iq 1.0000 test1 0.0138 1.0000 test2 0.0341 0.1449 1.0000 test3 0.0229 0.9309 0.4813 1.0000 test4 0.9015 0.4325 0.0903 0.4124 1.0000 iq test1 test2 test3 test4 statpack v4 PAGE 96 command: stepr --------------- purpose: produce stepwise regressions reference: "mathematical methods for digital computers", ralston and wilf, pages 191-203. description: the "stepr" command allows the user to produce stepwise regressions for selected variables. when instructed, the user enters the desired options separated by commas. possible options to "stepr" are: "anova"--analysis of variance "durwt"--durbin-watson test for autocorrelation "f-val"--indicate f values for entering or omitting a variable "force"--indicate variables to be forced into regression "resid"--store residuals "toler"--indicate a tolerance other than .0001 if no options are desired, type a . if the user has specified the "toler" option he will be asked to enter a tolerance. the normally assumed tolerance is .0001. if "f-val" option was specified, the user will be instructed to supply the f-value for omitting a variable. the "resid" option, if used, will cause the residuals to be stored as a variable. when asked under which variable the residuals should be stored, the user responds with a variable name (the variable name must already exist) or a variable number. once the residuals are stored the name of the variable containing the residuals will automatically be changed to "resid". the user will now be instructed to list the independent variables separated by commas for analysis by the stepwise regression. up to 19 variables may be listed by variable names (if names have been defined) or variable numbers. ranges of variables may be indicated by typing the extremes of the ranges separated by a "-". one or more "*" may be used when listing the variables to be analyzed. one at a time each variable not yet specified in the analysis will be substituted for every "*". those cases where the same variable would be listed twice in the same analysis will be eliminated, as will be those cases which, except for a change in the order of the variables, duplicate an statpack v4 PAGE 97 analysis already performed. the user will now be asked to enter the dependent variable, either the variable name (if names have been defined) or the variable number may be used. if the user wishes to substitute in one at a time all those variables not specified as independent, he may respond with a "*". the "*" may be used both as the dependent variable and as one or more independent variables in the same analysis. if the user specified the "force" option, he will be instructed to enter those variables, separated by commas to be forced into the stepwise regression. variables to be forced into the regression may be entered by either variable names (if names have been defined) or variable numbers. only variables specified as independent may be forced into the stepwise regression. example: which command? stepr list the options you wish separated by commas list the independent variables? sex,age,height,weight,gpa which is the dependent variable? iq ***** stepwise regression ***** 6 variables; variable: iq is dependent standard error of y = 17.45335 step no. 1 entering variable: weigh f-level 2.676 with prob. 0.1024 standard error of estimate 17.43 coefficient of determination = 0.4648738e-02 coefficient of multiple regression = 0.6818165e-01 increase in coefficient of determination = 0.4648738e-02 constant 95.825 variable coefficient std error of coeff weigh 0.03592 0.02196 statpack v4 PAGE 98 step no. 2 entering variable: age f-level 1.060 with prob. 0.3037 standard error on estimate 17.43 coefficient of determination = 0.5489679e-02 coefficient of multiple regression = 0.8055854e-01 increase in coefficient of determination = 0.1840942e-02 constant 102.00 variable coefficient std error of coef age -0.26949 0.26177 weigh 0.03545 0.02196 step no. 3 entering variable: heigh f-level 0.8806 with prob. 0.3484 standard error of estimate 17.43 coefficient of determination = 0.8019567e-02 coefficient of multiple regression = 0.8955203e-01 increase in coefficient of determination = 0.1529887e-02 constant 122.74 variable coefficient std error of coef age -0.29100 0.26280 heigh -0.38488 0.41014 weigh 0.06612 0.03937 step no. 4 entering variable: gpa f-level 0.1101 with prob. 0.7402 standard error of estimate 17.44 coefficient of determination = 0.8211069e-02 coefficient of multiple regression = 0.9061495e-01 increase in coefficient of determination = 0.1915023e-03 constant 121.44 variable coefficient std error of coef age -0.29444 0.26320 heigh -0.38449 0.41046 weigh 0.06558 0.03944 gpa 0.48003 1.44696 statpack v4 PAGE 99 step no. 5 entering variable: sex f level 0.4579661e-01 with prob. 0.8306 standard error of estimate = 17.45704 coefficient of determination = 0.8290887e-02 coefficient of multiple regression = 0.9105431e-01 increase in coefficient of determination = 0.7981807e-04 constant 121.2487 std.err. standardized var. coeff. of coeff. coefficient t-value prob. sex -0.3844 1.796 -0.1102009e-01 -0.2140 0.831 age -0.2917 0.2637 -0.4645334e-01 -1.106 0.269 heigh -0.3875 0.4110 -0.7074679e-01 -0.9427 0.346 weigh 0.6921e-01 0.4296e-01 0.1313598 1.611 0.108 gpa 0.4800 1.448 0.1388192e-01 0.3315 0.740 statpack v4 PAGE 100 command: stop -------------- purpose: restart stat pack, alter data size description: the "stop" command allows the user to restart a run of stat pack. once the command is given, no additional responses are necessary. all files except those created with a "store" command will be destroyed. output which has been assigned to the line printer but has not been printed, will remain unchanged, and any further output assigned to the printer will be added. when the "fini" command is given all output to that point will be printed. data which has been entered for analysis will have to be re-entered. the user will be given the opportunity to restate the limits for his data when the "stop" command is used. it is possible to increase, decrease, or leave unchanged the assumed data set; however, the size is still subject to the original limitations. example: which command? stop maximum number of observations? statpack v4 PAGE 101 command: store --------------- purpose: store data on disk limitations: data stored as floating point numbers, with no option available to alter output format. description: the "store" command allows the user to store selected variables on the disk under his own area. when the file name is requested, the user types in up to a six character name, and up to a three character extension separated by a period. next the user will be asked for the variables to be stored. to indicate the variables, list either the variable names (if names have been defined) or the variable numbers on one line separated by commas. ranges of variables may be indicated by typing the extremes of the range separated by a "-". if all the variables are to be stored, a "*" may be used. a standard protection code of 177 will be assigned to the file unless otherwise specified by the user. data will be stored according to the format (8g15.7). example: which command? store what is the name of the file? song.dat which variables? 1,3-5 selected variables were stored according to format: (8g15.7) what protection would you like? 177 statpack v4 PAGE 102 command: title --------------- purpose: label output limitation: the title is limited to one line of 72 characters. description: the "title" command allows the user to label output with a line of identification. when instructed, the user types in a label of up to 72 characters. once the "title" command has been issued, the output from each command will be labeled. only another "title" command can modify a header already entered. example: which command? title type in the line of identification data used is random and not meant for conclusions which command? desc data used is random and not meant for conclusions there are 1 variables and 14 observations var. means std.dev. variance 1 4.500000 1.911504 3.653846 statpack v4 PAGE 103 command: trans --------------- purpose: create or modify variables by combining or transforming existing variables. description: instructions for transforming variables are structured in the same manner as a fortran arithmetic statement. the basic form of each instruction is: the variable to be modified or created, a "=", and the expression to be evaluated. for each observation in the data set, the expression to the right of the "=" is evaluated and its final value is placed in the variable to the left of the "=". the rules governing the evaluation of the expression are the same as for fortran. the order in which operations are executed (hierarchy) is as follows: order sign explanation of sign ----- ---- ------------------- 1 ** exponent 2 * multiply 2 / divide 3 + add 3 - subtract operations which have the same order of execution are evaluated as they are encountered proceeding from left to right through the expression. parentheses inside an expression are evaluated first, beginning with the innermost. several predefined functions are available for use in the transformations. they are: "abs" - absolute value "arcsn"- arc sin "arctn"- arc tangent "cos" - cosine "exp" - exponential (e to the x) "ln" - natural log "log10"- log base 10 "mean" - mean of variable "norm" - normal random number generator "ran" - random number generator (.0-1.) "sin" - sin "sqrt" - square root "std" - standard deviation of variable functions are evaluated on an equal priority within parentheses. they are used by typing the abbreviation, and then the number or expression to be evaluated, enclosed in parentheses. statpack v4 PAGE 104 the "trans" command also allows a form of conditional statement, for which four comparisons to zero are available. these are: "ifl" - if less than zero "ife" - if equal to zero "ifn" - if not equal to zero "ifg" - if greater than zero conditional statements are written in three parts: a condition to be satisfied, indicated by the three-character code; an expression enclosed in parentheses to be evaluated and compared against zero; and the transformation to be executed if the conditional is satisfied. for each observation, the expression enclosed in parentheses is evaluated; if it has the relationship to zero indicated by the conditional code, the transformation is done for that observation. if the conditional code is not satisfied, no action is taken and the next observation is considered. when issuing instructions to "trans", variable names may be used or the variable numbers preceded by a "#". examples: ? total=pts1+pts2+pts3 the variable: total is created or modified by adding the variables: pts1, pts2, and pts3 together and placing the final value in total. ? avgpt=(pts1+pts2+pts3)/3. the variable: avgpt is created or modified by adding the variables: pts1, pts2, pts3 together, dividing the sum by 3 and placing the final answer in avgpt. ? iq=mtage/pyage the variable: iq is modified or created by dividing the variable: mtage by the variable: pyage and placing the answer in iq. ? z=(weigh-mean(weigh))/std(weigh) the variable: z is created or transformed by subtracting the mean of variable: weigh from the variable: weigh and dividing that value by the standard deviation of the variable: weigh. statpack v4 PAGE 105 ? log3=ln(#3) create or modify the variable: log3 by taking the natural log of variable number: 3. ? exp=3.14*sex+2.2*weigh+22. create or modify the variable: exp by placing the value of 3.14 times the variable: sex plus 2.2 times the variable: weigh plus 22 into the variable: exp. ? ifl(age-24) group=1 create or modify the variable: group by checking the variable: age. if the value of variable age minus 24 is less than 0, put a 1 in variable: group; otherwise leave group unchanged. statpack v4 PAGE 106 command: ttest --------------- purpose: calculate t tests (significant difference between means) reference: "statistical methods", snedecor and cochran, pages 104-106 description: the "ttest" command allows the user to calculate t tests (significant difference between means). when instructed, the user lists the options he desires separated by commas. possible options are: "headr"--suppress initial portion of report, that part containing means and standard deviations for each sample. "probs"--output probability (two-tailed) associated with t tests. "break"--select samples from one variable based on the value of a second variable. for each observation, the value of the second variable (breakdown variable) will be used to determine in which sample the value of variable being analyzed belongs. this is accomplished by determining which of a series of ranges the value of the breakdown variable fits into, and then moving the value of analysis variable to the corresponding sample. (if this option is not used, ttest will be calculated between variables.) note: the following options are used only if "break" has been used. "discr"--automatic breakdown. instead of the user entering ranges, a separate range will be created automatically for each value in the breakdown variable. "auto"--automatic breakdown. this option is the same as the "discr" option. do not enter "auto" with the other options, it should be entered only when asked to enter the ranges. note: the following option is only available if automatic breakdowns are to be used. "range"--list the ranges to be used for the automatic breakdown. if the "break" option has not been specified, t tests will be calculated between all possible pairs of variables. no other user responses will be necessary in this case. if the "break" option has been used, it will be necessary for the user to supply the following information: statpack v4 PAGE 107 (1) the variables for which t tests are to be calculated (up to 20). the samples for each set of t tests will be selected from a single variable. variables may be listed using either variable names (if names have been defined) or variable numbers. ranges of variables may be specified by listing the extremes of the range separated by a "-". where t tests are to be calculated for all variables, a "*" may be used instead of variable names or numbers. (2) the variable to be used for the breakdowns. only one variable may be used, it may be identified by either the variable name (if name has been defined) or variable number. all of the variables listed for analysis will be processed using the same breakdown variable. (3) ranges for the breakdown variable. if the "discr" option has been used, this information will be automatically calculated, and need not be supplied by the user. if the "discr" option has not been used, the user may still request the ranges to be automatically calculated by responding with "auto". to enter ranges, the user types the extremes of the range, smallest first, separated by a comma. only one range may be entered per line. up to 50 ranges may be entered. after the last range has been entered, the user types a ^z(control z). examples: which command? ttest enter options separated by commas ***** t tests ***** analysis run with each variable being used as a treatment var. size mean std. dev. iq 559 110.1 14.61 test1 559 41.75 21.74 test2 559 49.68 18.73 test3 559 47.88 12.28 test4 559 64.81 19.70 iq .0000 test1 -61.70 .0000 test2 -60.13 6.537 .0000 test3 -77.09 5,812 -1.896 .0000 test4 -43.66 18.59 13.16 17.24 .0000 iq test1 test2 test3 test4 which command? ttest statpack v4 PAGE 108 enter options separated by commas break,discr,range on what variables are the t-tests to be run? iq,height what is the variable to be used for the breakdown? sex ranges for breakdown variable: sex .0000 , .0000 1.000 , 1.000 ***** t tests ***** analysis of variable: iq with treatments determined by a breakdown on variable: sex var. size mean std. dev. 1 281 100.4 17.53 2 294 101.5 17.39 1 .0000 2 .7618 .0000 1 2 ***** t tests ***** analysis on variable: heigh with treatments determined by a breakdown on variable: sex var. size mean std. dev. 1 281 62.45 2.275 2 294 65.42 3.259 1 .0000 2 12.62 .0000 1 2 statpack v4 PAGE 109 command: type -------------- purpose: type selected variables on the terminal. description: the "type" command allows the user to display data on the terminal. when asked for the variables, the user responds by listing the desired variables on a line separated by commas. variables may be entered using either variable names (if names have been defined) or variable numbers. ranges of variables may be specified by listing the extremes of the range separated by a "-". where all variables are to be printed, use a "*" instead of variable names or numbers. the "print" command is also available in cases where the output to the terminal would be excessive. example: which command? type which variable? sex,age,3,5-6 var obs sex age 3 5 6 1 1.000 23.00 4.000 9.000 7.000 2 1.000 21.00 6.000 8.000 9.000 3 1.000 25.00 7.000 9.000 6.000 4 2.000 18.00 6.000 5.000 3.000 5 2.000 18.00 5.000 6.000 7.000 6 2.000 19.00 7.000 9.000 6.000 7 1.000 16.00 6.000 7.000 5.000 8 2.000 24.00 5.000 7.000 8.000 9 2.000 21.00 4.000 7.000 8.000 10 2.000 20.00 3.000 4.000 2.000 statpack v4 PAGE 110 command: wilcx --------------- purpose: use the wilcoxon matched-pairs signed-rank test to calculate mean, standard deviation, sample size, z-score, and t. reference: "basic statistical methods", downe and heath, pages 209, 210. "non-parametric statistics", siegel, pages 75-81. description: the "wilcx" command allows the user to use the wilcoxon matched-pairs signed-rank test to calculate the associated mean, standard deviation, sample size, z-score, and t for all possible pairs of variables. after the command has been given, no additional user responses are necessary. example: which command? wilcx ***** wilcoxon matched-pairs signed-rank test ***** var. vs var. mean s.d. n z t iq test1 78260.00 3820.40 559 -20.48 0.00 iq test2 78260.00 3820.40 559 -20.48 0.00 iq test3 78260.00 3820.40 559 -20.48 0.00 iq test4 78260.00 3820.40 559 -20.48 0.00 test1 test2 77701.50 3799.94 557 -6.48 53095.00 test1 test3 78260.00 3820.40 559 -10.93 36487.00 test1 test4 76590.50 3759.12 553 -17.75 9882.00 test2 test3 78260.00 3820.40 559 -2.35 69267.00 test2 test4 78260.00 3820.40 559 -11.97 32546.00 test3 test4 78260.00 3820.40 559 -16.26 16128.50 statpack v4 PAGE 111 command: xtab -------------- purpose: produce cross tabs (output is in the form of ordered pairs) description: the "xtab" command allows the user to tabulate one or more cross tabs. the user will first be asked if he desires percentages, to which the response must be a "yes" or "no". cross tabs may be produced for the following: (1) a single variable vs a single variable (2) a single variable vs all other variables (3) all variables vs all variables when instructed to enter the cross tabs, the user lists up to 20 cross tabs separated by semicolons. each cross tab is composed of two variables separated by a comma. to indicate the variables, either variable names (if names have been defined) or variable numbers may be used. where all variables are to be used, a "*" may be substituted for the variable names or numbers. the results will be adjusted in size for output to terminal or line printer. if a tabled version of the cross tab is desired see the command "xtab*". note: positive and negative numbers as well as multiple digit numbers may be processed with this command. examples: which command? xtab do you also want percentages (yes or no)? yes list the variables you wish to have cross tabs on each cross tab separated by a semi-colon and the variables of each cross tab separated by a comma sex,age statpack v4 PAGE 112 cross tab variable: sex vs variable: age var sex var age freq. percent ----------------------------------- .0000 18.00 27 4.7% .0000 19.00 28 4.9% .0000 20.00 23 4.0% .0000 21.00 36 6.3% .0000 22.00 30 5.2% .0000 23.00 22 3.8% .0000 24.00 26 4.5% .0000 25.00 30 5.2% .0000 26.00 25 4.3% .0000 27.00 34 5.9% .1000 18.00 18 3.1% .1000 19.00 21 3.7% .1000 20.00 35 6.1% .1000 21.00 28 4.9% .1000 22.00 36 6.3% .1000 23.00 30 5.2% .1000 24.00 38 6.6% .1000 25.00 34 5.9% .1000 26.00 29 5.0% .1000 27.00 25 4.3% which command? xtab do you also want percentages (yes or no)? no list the variable you wish to have cross tabs on each cross tab separated by a semi-colon and the variables of each cross tab separated by a comma sex,age cross tab variable: sex vs variable: age var sex var age freq. var sex var age freq. -------------------------- -------------------------- .0000 18.00 27 .0000 19.00 28 .0000 20.00 23 .0000 21.00 36 .0000 22.00 30 .0000 23.00 22 .0000 24.00 26 .0000 25.00 25 .0000 26.00 25 .0000 27.00 34 1.000 18.00 18 1.000 19.00 21 1.000 20.00 35 1.000 21.00 28 1.000 22.00 36 1.000 23.00 30 1.000 24.00 38 1.000 25.00 25 1.000 26.00 29 1.000 27.00 25 statpack v4 PAGE 113 command: xtab* --------------- purpose: produce cross tabs (output is a cross tab table) limitation: output must be assigned to line printer (see command "assign"). description: the "xtab*" command allows the user to tabulate one or more cross tabs. the user will first be asked if he desires percentages,to which the response must be a "yes" or "no". cross tabs may be produced for the following: (1) a single variable vs a single variable (2) a single variable vs all other variables (3) all variables vs all variables when instructed to enter the cross tabs, the user lists up to 20 cross tabs separated by semicolons. each cross tab is composed of two variables separated by a comma. to indicate the variables, either variables names (if names have been defined) or variable numbers may be used. where all variables are to be used, a "*" may be substituted for variable names or numbers. results will be in a tabled form only if output has been assigned to the line printer. if the "assign" command has not been used, the output will be in the form of ordered pairs. note: positive and negative numbers as well as multiple digit numbers may be processed with "xtab*". statpack v4 PAGE 114 example: which command? xtab* do you also want percentages (yes or no)? yes list the variables you wish to have cross tabs on each cross tab separated by a semi-colon and the variables of each cross tab separated by a comma age,sex cross tab variable: age vs variable: sex variable: age variable: sex value 0.000 1.00 -------------------- i 18.0 i 27 18 i 4.70% 3.13% i 19.0 i 28 21 i 4.87% 3.65% i 20.0 i 23 35 i 4.00% 6.09% i 21.0 i 36 28 i 6.26% 4.87% i 22.0 i 30 36 i 5.22% 6.26% i 23.0 i 22 30 i 3.83% 5.22% i 24.0 i 26 38 i 4.52% 6.61 i 25.0 i 30 34 i 5.22% 5.91% i 26.0 i 25 29 i 4.35% 5.04% i 27.0 i 34 25 i 5.91% 4.35% statpack v4 PAGE 115 command: zscor --------------- purpose: calculate z-scores. reference: "basic statistical methods", downe and heath, pages 60-61. description: the "zscor" command allows the user to calculate z-scores for one or more variables. when instructed, the user lists the variables separated by commas for which z-scores are to be calculated. up to 40 variables may be listed using either variable names (if names have been defined) or variable numbers. ranges of variables may also be indicated by typing the extremes of the range separated by a "-". where z-scores are to be calculated for all variables, a "*" may be substituted for the variable names and numbers. frequencies will be included in the output for the user's convenience. example: which command? zscor which variable: height ***** z scores for variable: heigh ***** value frequency z-score 58.00000 2 -1.873627 59.00000 45 -1.559810 60.00000 41 -1.245992 61.00000 57 -0.9321746 62.00000 50 -0.6183570 63.00000 70 -0.3045394 64.00000 69 0.9278121e-02 65.00000 63 0.3230957 66.00000 72 0.6369133 67.00000 31 0.9507308 68.00000 19 1.264548 69.00000 21 1.578366 70.00000 15 1.892184 71.00000 8 2.206001 72.00000 10 2.519819 73.00000 2 2.833636 statpack v4 PAGE 116 sample run #1 ------------- .r stp stat pack v4 western michigan university data limits are 100 observations and 7 variables do you wish to change these? (yes or no) no for a brief program description type "info" which command? fetch what is the file name and extension? test.dat how many input variables? 6 which command? desc there are 6 variables and 21 observations var. means std. dev. variance 1 26.57143 9.075084 82.35714 2 30.66667 8.302610 68.93333 3 30.85714 9.408962 88.52857 4 28.00000 8.191459 67.10000 5 27.52381 7.352680 54.06191 6 143.6190 24.29913 590.4476 which command? data how many input variables? 3 statpack v4 PAGE 117 enter input data 1,2,3 2,3,4 5,4,3 2,4,2 3,4,5 6,5,4 7,6,5 3,5,4 2,4,3 1,3,2 1,4,2 2,5,3 2,5,1 5,7,4 3,4,5 7,6,5 2,3,4 7,6,5 1,2,3 5,4,3 ^z which command? desc there are 3 variables and 20 observations var. means std. dev. variance 1 3.350000 2.158825 4.660526 2 4.300000 1.341641 1.800000 3 3.500000 1.192079 1.421053 which command? fini cpu time: 1.50 elapsed time: 3:0.55 no execution errors detected exit . statpack v4 PAGE 118 sample run #2 ------------- .r stp stat pack v4 western michigan university data limits are 100 observations and 7 variables. do you wish to change these? (yes or no) yes maximum number of observ.? 600 maximum number of variables? 10 for a brief description description type "info" which command? acbnk what bank name and switches? examp list bank codes separated by commas 1,2,3,4,5,6 which command? estat there are 6 variables and 575 observations var. means std.dev. variance sex 0.5113043 0.5003074 0.2503075 age 22.65391 2.779382 7.724963 heigh 63.97043 3.186565 10.15419 weigh 142.2348 33.12739 1097.424 iq 100.9339 17.45335 304.6193 gpa 2.988052 0.5047344 0.2547569 var. median mode maximum minimum sex 1.000000 1.000000 1.000000 0.0000000 age 23.00000 22.00000 27.00000 18.00000 heigh 64.00000 66.00000 73.00000 58.00000 weigh 139.0000 112.0000 251.0000 86.00000 iq 101.0000 113.0000 129.0000 70.00000 gpa 3.050000 2.910000 3.790000 1.850000 var. std err of mean skewness coef. of var. sex 0.2088243e-01 -0.4522899e-01 97.84924 age 0.1160092 -0.3795715e-01 12.26888 heigh 0.1330046 0.4152664 4.981309 weigh 1.382710 0.5287957 23.29064 iq 0.7284885 -0.9540812e-01 17.29185 statpack v4 PAGE 119 gpa 0.2106721e-01 -0.2985082 16.89175 which command? corr ***** correlation matrix ***** var. sex 1.0000 age 0.0298 1.0000 heigh 0.4663 -0.0661 1.0000 weigh 0.5833 -0.0209 0.8293 1.0000 iq 0.0318 -0.0443 0.0369 0.0682 1.0000 gpa 0.0417 0.0383 0.0533 0.0685 0.0169 1.0000 sex age heigh weigh iq gpa which command? ttest enter options separated by commas break,discr on what variables are the t-tests to be run? gpa what is the variable to be used for the breakdown? age ***** t tests ***** analysis on variable: gpa with treatments determined by a breakdown on variable: age var. size mean std. dev. 1 45 3.109 0.5089 2 49 2.942 0.4404 3 58 2.971 0.4685 4 64 2.946 0.5188 5 66 2.888 0.5115 6 52 2.902 0.5304 7 64 3.002 0.5373 8 64 3.017 0.5333 9 54 3.096 0.4939 10 59 3.039 0.4715 statpack v4 PAGE 120 1 .0000 2 -1.699 .0000 3 -1.424 .3255 .0000 4 -1.623 .4168e-01 -.2776 .0000 5 -2.239 -.5991 -.9411 -.6459 .0000 6 -1.947 -.4103 -.7216 -.4476 .1512 .0000 7 -1.041 .6344 .3397 .6008 1.244 1.001 .0000 8 -.8984 .7971 .5055 .7644 1.413 1.157 .1585 .0000 9 -.1297 1.656 1.369 1.594 2.249 1.942 .9756 .8224 .0000 10 -.7233 1.092 .7799 1.034 1.710 1.435 .4004 .2374 -.6247 .0000 1 2 3 4 5 6 7 8 9 10 which command? freq do you also want percentages (yes or no)? no which variables? age var. frequency ----- -------------------------------------------------------- age value 18.0 19.0 20.0 21.0 22.0 freq 45 49 58 64 66 value 23.0 24.0 25.0 26.0 27.0 freq 52 64 64 54 59 which command? pcent which variables? weight,height type in percentiles you wish to have, separated by commas dec statpack v4 PAGE 121 ***** percentiles ***** variables percentile weigh heigh ---------- ---------------------- 10.00 102.0 60.00 20.00 112.0 61.00 30.00 120.0 62.00 40.00 131.0 63.00 50.00 139.0 64.00 60.00 148.0 65.00 70.00 157.0 66.00 80.00 170.0 66.00 90.00 188.0 68.00 which command? plot which is the horizontal variable? weight which is the vertical variable? height plot of variable: weigh (horiz.) vs variable: heigh (vert.) i----------+---------+---------+---------+---------+ 73.00 + 1 1 i 221 12 1 1 i i 1 1 11 11 1 1 69.80 + 1 3 11111111 21 i 1212 121131311 1 i 1 1 1 22 231 1 11111 i 66.60 + 1 1122132521 5 1 21 1 i 1 1215541259545544231 i 1311131268733128513 111 i 12 2554673445575121 63.40 + i 15616625547834331 i 3 226331545443 131 i241162185526334 211 60.20 + 445213842422 i i137674663 1 1 i 1 1 57.00 + i---------+---------+---------+---------+---------+ 82.00 162.0 242.0 122.0 202.0 282.0 statpack v4 PAGE 122 which command? fini cpu time: 12.65 elapsed time: 19:2.27 no execution errors detected exit statpack v4 PAGE 123 sample run #3 ------------- .r stp stat pack v4 western michigan university data limits are 100 observations and 7 variables. do you wish to change these? (yes or no) no for a brief program description type "info" which command? data how many input variables? 5 enter input data 12,34,42,32,23 43,43,44,45,43 32,43,54,34,23 34,27,21,28,24 41,23,25,38,32 24,35,34,32,15 24,35,21,28,37 26,28,21,23,34 12,32,41,32,23 23,45,32,12,34 43,25,37,28,21 24,26,27,21,27 23,25,23,21,24 27,28,29,26,25 23,24,21,32,36 31,41,23,25,26 26,25,26,21,27 34,38,29,21,28 21,32,31,45 23,12,24,21,32 12,23,43,23,12 ^z statpack v4 PAGE 124 which command? manip ?? tv5o19 var. obs value 5 19 .000 ?? rv5o19 var. obs value new value 5 19 .000 ?32 ?? which command? name var 1? test1 var 2? test2 var 3? test3 var 4? test4 var 5? test5 which command? trans ?total=test1+test2+test3+test4+test5 variable: total has been created ? which command? anov1 list options separated by commas which variables? test1,test2,test3,test4,test5 ***** 1-way anova ***** tret. size mean std. dev. test1 21 26.57 9.075084 test2 21 30.67 8.302610 test3 21 30.86 9.408962 test4 21 28.00 8.191459 test5 21 27.52 7.352680 source sum of sq. d.f. mean sq. f prob between 313.3711 4 78.34 1.085 0.3680 within 7219.619 100 72.20 total 7532.990 104 statpack v4 PAGE 125 which command? estat there are 6 variables and 21 observations var. means std.dev. variance test1 26.57143 9.075084 82.35714 test2 30.66667 8.302610 68.93333 test3 30.85714 9.408962 88.52857 test4 28.00000 8.191459 67.10000 test5 27.52381 7.352680 54.06191 total 143.6190 24.29913 590.4479 var. median mode maximum minimum test1 24.00000 23.00000 43.00000 12.00000 test2 28.00000 25.00000 45.00000 12.00000 test3 29.00000 21.00000 54.00000 21.00000 test4 28.00000 21.00000 45.00000 12.00000 test5 27.00000 23.00000 43.00000 12.00000 total 140.0000 125.0000 218.0000 112.0000 var. std err of mean skewness coef. of var. test1 2.029250 0.2228182 34.15354 test2 1.856520 -0.3362000e-02 27.07373 test3 2.103908 0.8388538 30.49201 test4 1.831666 0.4848990 29.25521 test5 1.644109 -0.5015288e-01 26.71389 total 5.433451 1.428420 16.91916 which command? ttest enter options separated by commas probs ***** t tests ***** analysis run with each variable being used as a treatment var. size mean std. dev. test1 21 26.57 9.075 test2 21 30.67 8.303 test3 21 30.86 9.409 test4 21 28.00 8.191 test5 21 27.52 7.353 total 21 143.6 24.30 statpack v4 PAGE 126 test1 .0000 1.000p test2 1.526 .0000 .135p 1.000p test3 1.502 .6956e-01 .0000 .141p .945p 1.000p test4 .5355 -1.048 -1.050 .0000 .595p .301p .300p 1.000p test5 .3737 -1.299 -1.279 -.1982 .0000 .711p .202p .208p .844p 1.000p total 20.68 20.16 19.83 20.66 20.96 .000p -.000p .000p .000p .000p .0000 1.000p test1 test2 test3 test4 test5 total which command? corrt ***** correlated t ***** test1 0.0000 test2 1.656 0.0000 test3 1.447 0.9122e-01 0.0000 test4 0.6143 -1.148 -1.298 0.0000 test5 0.4537 -1.417 -1.109 -0.2229 0.0000 total 26.21 26.20 24.56 26.98 23.92 0.0000 test1 test2 test3 test4 test5 total which command? corr ***** correlation matrix ***** var. test1 1.0000 test2 0.1513 1.0000 test3 -0.0780 0.4218 1.0000 test4 0.2415 0.1669 0.3497 1.0000 test5 0.3287 0.1611 -0.3414 0.2100 1.0000 total 0.5758 0.6665 0.5167 0.6833 0.4190 1.0000 test1 test2 test3 test4 test5 total statpack v4 PAGE 127 which command? hist which variables? total ***** histogram for variable: total ***** 60.00 + i i i ixxxxxi i ixxxxxi 45.00 + ixxxxxi i ixxxxxi i ixxxxxi i ixxxxxi i ixxxxxi 30.00 + ixxxxxi i ixxxxxi i ixxxxxixxxxxi i ixxxxxixxxxxi i ixxxxxixxxxxi 15.00 + ixxxxxixxxxxixxxxxi i ixxxxxixxxxxixxxxxi i ixxxxxixxxxxixxxxxi i ixxxxxixxxxxixxxxxixxxxxi ixxxxxi i ixxxxxixxxxxixxxxxixxxxxi ixxxxxi --+-----+-----+-----+-----+-----+-----+ ^ 5 ^ 11 ^ 3 ^ 1 ^ 0 ^ 1 ^ ^ ^ ^ ^ ^ ^ ^ ^ 132. ^ 172. ^ 212. ^ 112. 152. 192. 232. which command? store what is the name of the file? test.dat which variables? test1-total selected variables were stored according to format: (8g15.7) what protection would you like? 155 which command? assign output assigned to printer which command? estat statpack v4 PAGE 128 which command? plot which is the horizontal variable? * which is the vertical variable? * which command? corr which command? fini cpu time: 17.12 elapsed time: 17:13.53 no execution errors detected exit . statpack v4 PAGE 129 glossary -------- binary--numbers which are represented in base 2 notation; when associated with file structures, those files which are word-oriented rather than ascii. bivariate--two variable brackets--[ ], contains the project-programmer number when reading files from another area. connect time--amount of time transpired between the user logging in and logging out. control z--special character typed by holding down the control button and typing a z. the control z is the end-of-file mark for the terminal. cpu time--amount of time the central processor (computer) actually spent doing the analysis. data--any or all facts, numbers, letters, or symbols which can be processed or produced by a computer; source information. data set--in the write-up, the data which is presently being analyzed; i.e., the data in core. disk--high-speed auxiliary storage device, on which information is recorded on the magnetizable surface of a rotating disk. expression--a string of variables and constant values separated by algebraic operations. a single term or two or more terms combined, by algebraic operators in accordance with the defined rules. extremes--maximum and minimum file extension (extension)--that portion of the file reference which follows the period in the name. maximum of three characters, usually refers to the type of file. file name (name)--that portion of the files reference which precedes the period in the name. maximum of six characters. format--the arrangement of information on a form or in storage. standard format for input is assumed to be (20f). hierarchy--the order in which different operations are executed in an expression. input--data to be processed; the process of transferring data from an external storage to an internal storage. statpack v4 PAGE 130 listing--output printed on line printer. magtape--abbreviation for magnetic tape, a large capacity storage medium obtainable from the computer center. magtape drive--the electro mechanical unit on which a magnetic tape is mounted prior to accessing it. major sort key--the variable to which the highest priority is assigned when ordering. minor sort key--the variable to which the least priority is assigned when ordering. missing data--data where values were not available. observation--case. octal--numbers which are represented in base 8 notation. ordered pairs--a pair of numbers where the order of occurrence indicates the variable they were chosen from. output--results or answers written to an output device (line printer, terminal, or disk). the process of transferring from an internal storage to an external media. protection code--a three-digit octal value which defines who may access, write on, or read a file. run--in stp, it refers to the time elapsed between typing of "r stp" and "fini". scaling--picking beginning points and increments which will fit into the space available and are easily examined. scan--to look at each piece of information in the set. to examine every entry routinely as the first part of a retrieval scheme. sort--to sequence or order observations according to a key contained in each observation. sort key--the variables in the observation which determine or are used to determine the order in which the observations occur. terminal--teletype, crt terminal user area--that portion of the disk allocated to a particular project- programmer number. variable name--user specified names for variables. statpack v4 PAGE 131 --carriage return. statpack v4 PAGE 132 index 1wayr . . . . . . . . . . . . . . . . . . . . . . 80 acbnk . . . . . . . . . . . . . . . . . . . . . . 7 anoc1 . . . . . . . . . . . . . . . . . . . . . . 12 anov1 . . . . . . . . . . . . . . . . . . . . . . 16 anov2 . . . . . . . . . . . . . . . . . . . . . . 20 assign . . . . . . . . . . . . . . . . . . . . . . 26 bargr . . . . . . . . . . . . . . . . . . . . . . 27 basic . . . . . . . . . . . . . . . . . . . . . . 29 chisq . . . . . . . . . . . . . . . . . . . . . . 30 copys . . . . . . . . . . . . . . . . . . . . . . 36 corr . . . . . . . . . . . . . . . . . . . . . . . 37 corrt . . . . . . . . . . . . . . . . . . . . . . 38 cvsmt . . . . . . . . . . . . . . . . . . . . . . 39 data . . . . . . . . . . . . . . . . . . . . . . . 42 deass . . . . . . . . . . . . . . . . . . . . . . 43 desc . . . . . . . . . . . . . . . . . . . . . . . 44 erana . . . . . . . . . . . . . . . . . . . . . . 45 estat . . . . . . . . . . . . . . . . . . . . . . 46 facto . . . . . . . . . . . . . . . . . . . . . . 47 fetch . . . . . . . . . . . . . . . . . . . . . . 52 fini . . . . . . . . . . . . . . . . . . . . . . . 53 form . . . . . . . . . . . . . . . . . . . . . . . 54 freq . . . . . . . . . . . . . . . . . . . . . . . 55 glossary . . . . . . . . . . . . . . . . . . . . . 129 help . . . . . . . . . . . . . . . . . . . . . . . 56 hist . . . . . . . . . . . . . . . . . . . . . . . 57 info . . . . . . . . . . . . . . . . . . . . . . . 59 kendl . . . . . . . . . . . . . . . . . . . . . . 60 kolm . . . . . . . . . . . . . . . . . . . . . . . 61 list of commands . . . . . . . . . . . . . . . . . 4 mabnk . . . . . . . . . . . . . . . . . . . . . . 66 make . . . . . . . . . . . . . . . . . . . . . . . 67 manip . . . . . . . . . . . . . . . . . . . . . . 68 mann . . . . . . . . . . . . . . . . . . . . . . . 74 mta/i . . . . . . . . . . . . . . . . . . . . . . 76 name . . . . . . . . . . . . . . . . . . . . . . . 79 statpack v4 PAGE 133 pcent . . . . . . . . . . . . . . . . . . . . . . 81 pcorr . . . . . . . . . . . . . . . . . . . . . . 83 plot . . . . . . . . . . . . . . . . . . . . . . . 84 print . . . . . . . . . . . . . . . . . . . . . . 86 prob . . . . . . . . . . . . . . . . . . . . . . . 87 program transfer . . . . . . . . . . . . . . . . . 6 ptbis . . . . . . . . . . . . . . . . . . . . . . 90 regr . . . . . . . . . . . . . . . . . . . . . . . 92 sample run #1 . . . . . . . . . . . . . . . . . . 116 sample run #2 . . . . . . . . . . . . . . . . . . 118 sample run #3 . . . . . . . . . . . . . . . . . . 123 sort . . . . . . . . . . . . . . . . . . . . . . . 94 srank . . . . . . . . . . . . . . . . . . . . . . 95 stepr . . . . . . . . . . . . . . . . . . . . . . 96 stop . . . . . . . . . . . . . . . . . . . . . . . 100 store . . . . . . . . . . . . . . . . . . . . . . 101 table of variable-observation combinations . . . . 3 title . . . . . . . . . . . . . . . . . . . . . . 102 trans . . . . . . . . . . . . . . . . . . . . . . 103 ttest . . . . . . . . . . . . . . . . . . . . . . 106 type . . . . . . . . . . . . . . . . . . . . . . . 109 wilcx . . . . . . . . . . . . . . . . . . . . . . 110 xtab . . . . . . . . . . . . . . . . . . . . . . . 111 xtab* . . . . . . . . . . . . . . . . . . . . . . 113 zscor . . . . . . . . . . . . . . . . . . . . . . 115