1. Let’s continue to review some of the statistics you’ve learned in your first class:
Bivariate analyses (two variables measured at a time on each observation) are done both graphically and numerically. There are 3 ways to look at the bivariate analyses:
categorical vs categorical (use PROC FREQ and PROC GCHART)
categorical vs quantitative (use PROC UNIVARIATE with the BY statement on the categorical variable - also PROC BOXPLOT and PROC TTEST & NPAR1WAY)
quantitative vs quantitative (use PROC GPLOT, PROC CORR, PROC REG)

2. /* for two categorical variables… */
PROC FREQ; TABLES marsh*form; run; quit;
PROC GCHART; VBAR marsh/ group=form; run; quit; /* what does the next one do? */
PROC GCHART; VBAR marsh/ sumvar=plantht type=mean group=form; run; quit;
/* now one categorical, one quantitative */
PROC SORT; BY marsh;
PROC UNIVARIATE DATA=padgett PLOT; VAR plantht; BY marsh; run; quit;
/* this gives side-by-side BOXPLOTS - can also use PROC BOXPLOT after SORTing */
PROC BOXPLOT DATA=padgett;
PLOT plantht*marsh; run; quit;

3. Now what about two quantitative variables??
/* first plot the two */
PROC GPLOT DATA=padgett;
PLOT totmass*plantht; run; quit;
/* get the correlation coefficients */
PROC CORR; run; quit;
/*this gives descriptive statistics and correlations of all numeric statistics*/
PROC REG; MODEL totmass = plantht;
PLOT totmass*plantht; run; quit; /* there are many options to REG */