＃11.1

numSummary(obarowStory1[,c("gnsc1.1", "gnsc1.2")], groups=obarowStory1$Treatment1, statistics=c("mean", "sd"))

summary(obarowStory1)

＃11.1.1

plotMeans(obarowStory1$gnsc1.1, obarowStory1$musict1, obarowStory1$picturest1, error.bars="conf.int")

obarowStory1$Treatment1

4 Levels: −M−P −M+P +M−P +M+P

obarowStory1$Treatment1=ordered(obarowStory1$Treatment1, levels= c("-M+P", "+M+P", "+M-P", "-M-P"))

＃11.2

new.obarow <- subset(obarow, subset=PRETEST1<18)

obarow$MusicT1 <- recode(obarow$trtmnt1, '1="no music"; 2="no music"; 3="yes music"; 4="yes music"; ', as.factor.result=TRUE)

＃11.3

y=Gender + Music + Pictures + Gender*Music + Gender*Pictures + Music*Pictures + Gender*Music*Pictures

summary(AnovaModel.6))

#11.3.2

attach(obarow) model=aov(gnsc1.1~gender*MusicT1*PicturesT1) summary(model)

model2=update(model,~.-gender:MusicT1:PicturesT1)

anova(model,model2)

summary(model2)

model3=update(model2,~.- gender:PicturesT1) anova(model2,model3)

model8=aov(gnsc1.1~1) anova(model7,model8)

summary(model7)

summary.lm(model7)

boot.stepAIC(model,data=obarow)

model9=aov(gnsc1.1~gender+MusicT1+gender:MusicT1) summary.lm(model9)

summary(model9)

anova(model7,model9)

plot(model7) detach(obarow)

model.adj=aov(gnsc1.1[-c(3,14,48)]~gender[-c(3,14,48)],data=obarow) summary.lm(model.adj)

#11.4

attach(Writing) tapply(score,list(L1,condition),mean)

write=lm(score~L1*condition) Anova(write)

summary(write)

levels(L1)
[1] "Arabic" "Japanese" "Russian" "Spanish"

 pairwise.t.test(score,L1, p.adjust.method="fdr”)

pairwise.t.test(score,condition, p.adjust.method="fdr”)

pairwise.t.test(score,L1:condition, p.adjust.method="fdr")

 pairwise.t.test(score,L1:condition, p.adjust.method="none")

＃11.6


grp<-c(2,3,5,8,4,1,6,7)