library(car)
library(MASS)
source("http://www.statpower.net/Content/312/R Stuff/Steiger R Library Functions.txt")
spss.data <- read.table("http://www.statpower.net/Content/312/Lecture Slides/spss.discrim.txt",header=T,sep = ",")
fb.data <- read.table("http://www.statpower.net/Content/312/Lecture Slides/football.txt",header=T,sep=",")
iris.data <- read.table("http://www.statpower.net/Content/312/Lecture Slides/IrisData.txt",header=T)
## spss Data 
##             Group 1 = customer service
##             Group 2 = mechanic
##             Group 3 = dispatcher
## FB Data   
##             Group 1 = HS fb player
##             Group 2 = College fb player
##             Group 3 = not a fb player
## Iris Data
##             Group 1 = Virginica
##             Group 2 = Versicolor
##             Group 3 = Setosa


## Analyze SPSS data
## ##################################
## Create x,D,H,and Group matrices
#####################################
names(spss.data)
x <- as.matrix(spss.data[1:3])
Group <- as.matrix(spss.data[,4:4])
DiscriminantAnalysis(x,Group)


## Analyze FB data
## ##################################
## Create x,D,H,and Group matrices
#####################################
names(fb.data)
x <- as.matrix(fb.data[,2:7])
Group <- as.matrix(fb.data[,1:1])
DiscriminantAnalysis(x,Group)

## Analyze Iris Data -- TRY IT!

## stepwise discriminant analysis
library(klaR)
football.data <- read.table("football.txt",header=T,sep=",")
fit <- greedy.wilks(GROUP ~ .,data=fb.data,niveau = .10)