> tapply(ethics,gender,mean) 1 2 32.51429 37.17617 > tapply(ethics,rank,mean) 1 2 38.30000 31.17349 > tapply(ethics,list(gender,rank),mean) 1 2 1 37.3 30.60000 2 43.1 34.39937 > > ethics.mod1 <- aov(ethics ~ gender*rank) > anova(ethics.mod1) Analysis of Variance Table Response: ethics Df Sum Sq Mean Sq F value Pr(>F) gender 1 861 860.90 6.0342 0.01461 * rank 1 3048 3047.64 21.3616 5.693e-06 *** gender:rank 1 34 34.10 0.2390 0.62526 Residuals 295 42087 142.67 --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 > summary.lm(ethics.mod1) Call: aov(formula = ethics ~ gender * rank) Residuals: Min 1Q Median 3Q Max -28.75 -7.84 -0.90 7.92 32.43 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 37.300 1.408 26.498 < 2e-16 *** gender2 5.800 3.390 1.711 0.0882 . rank2 -6.700 1.666 -4.023 7.32e-05 *** gender2:rank2 -2.001 4.092 -0.489 0.6253 --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Residual standard error: 11.94 on 295 degrees of freedom Multiple R-squared: 0.08565, Adjusted R-squared: 0.07636 F-statistic: 9.212 on 3 and 295 DF, p-value: 7.639e-06 > > ethics.mod2 <- lm(ethics ~ gender1 + rank1 + gr1) > summary(ethics.mod2) Call: lm(formula = ethics ~ gender1 + rank1 + gr1) Residuals: Min 1Q Median 3Q Max -28.75 -7.84 -0.90 7.92 32.43 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 36.3498 1.0230 35.533 < 2e-16 *** gender1 -2.3998 1.0230 -2.346 0.019642 * rank1 3.8502 1.0230 3.764 0.000202 *** gr1 -0.5002 1.0230 -0.489 0.625261 --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Residual standard error: 11.94 on 295 degrees of freedom Multiple R-squared: 0.08565, Adjusted R-squared: 0.07636 F-statistic: 9.212 on 3 and 295 DF, p-value: 7.639e-06 > anova(ethics.mod2) Analysis of Variance Table Response: ethics Df Sum Sq Mean Sq F value Pr(>F) gender1 1 861 860.90 6.0342 0.01461 * rank1 1 3048 3047.64 21.3616 5.693e-06 *** gr1 1 34 34.10 0.2390 0.62526 Residuals 295 42087 142.67 --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 > > options(contrasts=c("contr.sum","contr.poly")) > ethics.mod3 <- aov(ethics ~ gender + rank + gender:rank) > anova(ethics.mod3) Analysis of Variance Table Response: ethics Df Sum Sq Mean Sq F value Pr(>F) gender 1 861 860.90 6.0342 0.01461 * rank 1 3048 3047.64 21.3616 5.693e-06 *** gender:rank 1 34 34.10 0.2390 0.62526 Residuals 295 42087 142.67 --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 > summary.lm(ethics.mod3) Call: aov(formula = ethics ~ gender + rank + gender:rank) Residuals: Min 1Q Median 3Q Max -28.75 -7.84 -0.90 7.92 32.43 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 36.3498 1.0230 35.533 < 2e-16 *** gender1 -2.3998 1.0230 -2.346 0.019642 * rank1 3.8502 1.0230 3.764 0.000202 *** gender1:rank1 -0.5002 1.0230 -0.489 0.625261 --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Residual standard error: 11.94 on 295 degrees of freedom Multiple R-squared: 0.08565, Adjusted R-squared: 0.07636 F-statistic: 9.212 on 3 and 295 DF, p-value: 7.639e-06 > > #install.packages("car") > library(car) Warning message: package ‘car’ was built under R version 3.1.2 > > Anova(ethics.mod3,type="III") Anova Table (Type III tests) Response: ethics Sum Sq Df F value Pr(>F) (Intercept) 180136 1 1262.6123 < 2.2e-16 *** gender 785 1 5.5034 0.019642 * rank 2021 1 14.1652 0.000202 *** gender:rank 34 1 0.2390 0.625261 Residuals 42087 295 --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 >