Let’s review some of the statistics you’ve learned in your first class: Univariate analyses (single variable) are done both graphically and numerically. For categorical variables, use bar graphs and percentages. SAS does this with PROC GCHART and PROC FREQ PROC GCHART DATA=padgett; VBAR marsh; title ‘Vertical Bar Graph’; PROC GCHART DATA=padgett; HBAR marsh; title ‘Horizontal Bar Graph’; PROC GCHART DATA=padgett; HBAR plantht; title ‘Histogram (sort of)’; *choose your own midpoints with the option /midpoints= a to b by … ; PROC FREQ DATA=padgett; TABLES marsh type flower; run; quit;

For quantitative variables, use histograms, stem and leaf plots, boxplots (especially for comparisons - more later), quantile plots (probability plots). SAS does this with PROCs UNIVARIATE, MEANS, SUMMARY, TABULATE, REPORT, etc. Right now, we’ll concentrate on UNIVARIATE: PROC UNIVARIATE DATA=padgett; VAR plantht totmass; title ‘Lots of Statistics…’; run; quit; PROC UNIVARIATE DATA=padgett NORMAL PLOT; VAR plantht totmass; title ‘With the NORMAL and PLOT options’; run; quit; *Better histogram is done in UNIVARIATE with the HISTOGRAM statement; PROC UNIVARIATE DATA=padgett; VAR plantht totmass; HISTOGRAM plantht /MIDPOINTS 0 to 150 by 25 NORMAL; INSET MEAN=‘Mean’ (7.2) STD=‘Standard Deviation’ (7.2)/Font=‘Courier’ POS=NW HEIGHT=3; run; quit;

UNIVARIATE also gives very nice normal quantile and normal probability plots: PROC UNIVARIATE DATA=padgett; VAR plantht totmass; QQPLOT totmass; PROBPLOT plantht; run; quit;