SOME BASIC MINITAB COMMANDS

mtb> set 'file.dat' c1            (Note: read single variable data from file)
mtb> read 'file.dat' c1,...,ck    (Note: read data from file, put into columns)
mtb> print c1,...,ck              (Note: print the data for each column)
mtb> describe c1,...,ck           (Note: provide basic statistics for each col)
mtb> histogram c1,...,ck          (Note: histograms, one for each data column)
mtb> plot c1 c2                   (Note: scatter plot of y in c1 vs x in c2)
mtb> lplot c1 c2, labels in c3    (Note: scatter plot with labels in c3)
mtb> nscores c11, put into c12    (Note: obtain normal scores for data in c11)
mtb> correlation c1 c2
mtb> correlation c1,...,ck
mtb> oneway c2, c2                (Note: one-way ANOVA for data c1, codes in c2)
mtb> stop                         (Note: end the current Minitab session)

SPECIFIC MINITAB COMMANDS FOR REGRESSION ANALYSIS

mtb> regress c1 on k predictors c2,...,c(k+1);
        resid in c11;             (Note: Residuals in c11)
        fits in c12.               (Note: Fitted values in c12)
        sresid in c13;            (Note: Standardized residuals in c13)
        tresid in c14;            (Note: Studentized residuals in c14)
	cookd in c15;             (Note: Cook's distance statistic in c15)
	hi in c16;                (Note: Leverage values h_(i,i) in c16)
mtb> stepwise c1 on predictors c2,...,c(k+1)     (Note: Stepwise regression)
mtb> bregression c1 on predictors c2,...,c(k+1)  (Note: Best subset regression)