> (tapply(ex_tol,list(gender,smoke,fat),mean)) , , Low Light Heavy Male 25.96667 19.86667 Female 19.83333 12.13333 , , High Light Heavy Male 14.06667 16.03333 Female 12.06667 10.20000 > (tapply(ex_tol,list(gender,fat),mean)) Low High Male 22.91667 15.05000 Female 15.98333 11.13333 > (tapply(ex_tol,list(gender,smoke),mean)) Light Heavy Male 20.01667 17.95000 Female 15.95000 11.16667 > (tapply(ex_tol,list(fat,smoke),mean)) Light Heavy Low 22.90000 16.00000 High 13.06667 13.11667 > (tapply(ex_tol,gender,mean)) Male Female 18.98333 13.55833 > (tapply(ex_tol,fat,mean)) Low High 19.45000 13.09167 > (tapply(ex_tol,smoke,mean)) Light Heavy 17.98333 14.55833 > > > stress.aov1 <- aov(ex_tol ~ gender*fat*smoke) > anova(stress.aov1) Analysis of Variance Table Response: ex_tol Df Sum Sq Mean Sq F value Pr(>F) gender 1 176.584 176.584 18.9155 0.0004971 *** fat 1 242.570 242.570 25.9839 0.0001076 *** smoke 1 70.384 70.384 7.5394 0.0143574 * gender:fat 1 13.650 13.650 1.4622 0.2441432 gender:smoke 1 11.070 11.070 1.1859 0.2922989 fat:smoke 1 72.454 72.454 7.7612 0.0132205 * gender:fat:smoke 1 1.870 1.870 0.2004 0.6604336 Residuals 16 149.367 9.335 --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1