get all the 4 steps and extras for this problem Problem 2: > summary(aov(score~group)) Df Sum Sq Mean Sq F value Pr(>F) group 2 474.1 237.1 32.04 1.54e-05 *** Residuals 12 88.8 7.4 --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 > M=tapply(score, group, mean) > sd=tapply(score, group, sd) > n=tapply(score,group,length) > se= sd/sqrt(n) > cbind(mean=M,std.dev=sd,std.error=se, n=n) mean std.dev std.error n 1condom 21.8 3.834058 1.7146428 5 2abstinence 35.0 1.581139 0.7071068 5 3control 25.0 2.236068 1.0000000 5 > pairwise.t.test(score, group, p.adjust.method ="bonferroni") Pairwise comparisons using t tests with pooled SD data: score and group 1condom 2abstinence 2abstinence 1.7e-05 - 3control 0.26270 0.00025 P value adjustment method: bonferroni