# 1a
mat<-matrix(data=c(3,5,7,4,3,
                   2,5,8,6,5,
                   7,3,5,3,4),
      ncol=5,nrow=3,byrow="TRUE")
mat

# 1b
colnames(mat)<-c("one", "two", "three", "four", "five")
rownames(mat)<-c("Alice", "Bill", "Sue")
mat

# 1c
mean(mat[2,])

#or 

mean(mat["Bill",])


# 1d
RowMeans<-apply(mat,MARGIN=1,FUN=mean)
RowMeans
mat<-cbind(mat,RowMeans)
mat

# 2a
Sex<-rep(c("Male","Female"),each=4)
Commsize<-c("Small","Large","Small","Large",
            "Large","Large","Small","Small")
Altruism<-c(3,6,8,4,5,8,3,2)
newdat<-data.frame(Sex,Commsize,Altruism)
newdat

# 2b
setwd("C:/Users/cribbie/Dropbox/Courses/Intro to R/SCS_2016")
write.csv(newdat,file="myfile.csv")

# 2c
dat1<-read.csv(file.choose())
dat1

# 2d
dat2<-subset(dat1, Sex=="Male" & Commsize=="Large")
mean(dat2$Altruism)

#or

mean(dat1$Altruism[Sex=="Male" & Commsize=="Large"])

# 2e
median(dat1$Altruism[Sex=="Female"])

# 2f
is.factor(dat1$Commsize)

# 2g
hist(dat1$Altruism)
hist(dat1$Altruism,breaks=6)

# 2h
library(car)
leveneTest(y=dat1$Altruism,group=dat1$Sex)

# 2i
dat1
dat1$Altruism[1]<-9

## need xquartz if working with a mac
dat2<-edit(dat1)
dat2<-fix(dat1)

#or

dat2<-dat1
dat2$Altruism[1]<-9
dat2

# 3
sq<-function (x) {
  squ<-x*x
  return(squ)}
sq(5)
sq(x=5)