setwd("~/Dropbox/courses/5210-2022/web-5210/psy5210/Projects/Chapter16")
specialty.0 <- c("Advertising","Advertising","Advertising","Advertising","Advertising",
"Business","Business","Business","Business","Business",
"Certification","Certification","Certification","Certification","Certification")
specialty <- as.factor(c("Advertising","Advertising","Advertising","Advertising","Advertising",
"Business","Business","Business","Business","Business",
"Certification","Certification","Certification","Certification","Certification"))
salary <- c(30,35,32,40,34,70,56,45,65,28,19,23,28,18,32)
c1 <- specialty=="Advertising"
c1
c2 <- specialty=="Business"
c3 <- specialty=="Certification"
c1
c2
c3
c2 <- specialty=="Business"*1
c2 <- specialty=="Business"+1
c2 <- (specialty=="Business")+0
c2
c3 <- (specialty=="Certification") + 0
c1 <- (specialty=="Advertising") + 0
c1
c2
c3
lm(salary~c1+c2+c3)
lm(salary~specialty)
lm(salary~0+c1+c2+c3)
lm(salary~specialty)
lm(salary~specialty+0)
lm(salary~0+c1+c2+c3)
contr.treatment(3)
contr.treatment(5)
advertising
specialty
lm(salary~specialty+0)$fit
lm(salary~0+c1+c2+c3)$fit
boxplot(salary~specialty)
summary(lm(salary~0+c1+c2+c3))
summary(lm(salary~c1+c2+c3))
boxplot(salary~specialty)
summary(lm(salary~specialty))
contr.helmert(levels(specialty))
contrasts(specialty)<- contr.helmert(levels(specialty))
summary(lm(salary~specialty))
contr.helmert(5)
contr.helmert(levels(specialty))
contrasts(specialty)<- contr.helmert(levels(specialty))
lm(salary~specialty)
summary(lm(salary~specialty))
values <- c(1,1.1,1,1.3,.9,1.2, 4,5,6,8,10,9)
months <- as.factor(c("Jan","Feb","Mar","Apr","May","Jun","July","Aug","Sep","Oct","Nov","Dec"))
months
contrasts(months) <- contr.helmert(levels(months))
barplot(values,names=months)
lm(values~months)
contrasts(months)
months.0 <- c("Jan","Feb","Mar","Apr","May","Jun","July","Aug","Sep","Oct","Nov","Dec")
months<- factor(months.0,levels=months.0)
months
contrasts(months) <- contr.helmert(levels(months))
constrasts(months)
contrasts(months)
lm(values~months)
summary(lm(values~months))
contr.sdif(3)
library(MASS)
contr.sdif(3)
contr.sdif(4)
cont.helmert(4)
contr.helmert(4)
contr.sdif(4)
cc <- contr.sdif(4)
cc[,1] * cc[,2]
sum(cc[,1] * cc[,2])
contrasts(months) <- contr.sdif(months)
lm(values~months)
contr.sum(3)
contrasts(specialty)<-contr.sum(levels(specialty))
lm(salary~specialty)
15.8-2.8
anova(lm(salary~specialty))
summary(lm(salary~specialty))
aov(salary~specialty)
summary(lm(salary~specialty))
aov(salary~specialty)
anova(lm(salary~specialty))
summary(aov(salary~specialty))
x <- sample(LETTERS,100,replace=T)
x
table(x)
length(table(x))
x <- sample(LETTERS[1:25],100,replace=T)
x
table(x)
factor(x)
sort(factor(x))
factor(x,levels=LETTERS)
table(factor(x,levels=LETTERS))
rev(LETTERS)
table(factor(x,levels=rev(LETTERS)))
(factor(x,levels=rev(LETTERS)))
xx <- (factor(x,levels=rev(LETTERS)))
xx
x
x <- sample(c("M","T","W","TH","F"),100,replace=T)
x
as.factor(x)
as.factor(x,levels=c("M","T","W","TH","F"))
factor(x,levels=c("M","T","W","TH","F"))
factor(x,levels=c("M","T","W","TH"))