dean.df <- read.csv(paste(“Deans Dilemma.csv”, sep=“”)) View(dean.df)

summary(dean.df) describe(dean.df)

median(dean.df\(Salary) table(dean.df\)Placement)

prop.table(dean.df\(Placement_B,dean.df\)Placement) with(dean.df, prop.table(table(Placement_B==“1”)))

mydata <-with(dean.df,table(Placement_B)) View(mydata)

placed <- dean.df[dean.df$Placement_B==“1”,] View(placed)

median(dean.df\(Salary [dean.df\)Placement_B==“1”]) table(mean(dean.df\(Salary[dean.df\)Gender==“F” & dean.df\(Placement_B=="1"])) table(mean(dean.df\)Salary[dean.df\(Gender=="M" & dean.df\)Placement_B==“1”]))

notplaced <- dean.df[dean.df$Placement_B==“0”,] View(notplaced)

placedET <- dean.df[dean.df\(Placement_B=="1" & dean.df\)S.TEST==“1” , ] View(placedET)

hist(placed$Percent_MBA, main=“MBA Performance of placed students”, breaks=3, xlab=“MBA Percentage”, ylab=“Count”, col=“blue”)

par(mfrow=c(1,2)) hist(placed\(Percent_MBA, main="MBA Performance of placed students", breaks=3, xlab="MBA Percentage", ylab="Count", col="blue") hist(notplaced\)Percent_MBA, main=“MBA Performance of placed students”, breaks=3, xlab=“MBA Percentage”, ylab=“Count”, col=“blue”)

boxplot(dean.df\(Salary ~ dean.df\)Gender, horizontal=TRUE, ylab=“Gender”, xlab=“Salary”, las=1, main=“Comparison of salaries of males and females”)

scatterplotMatrix(formula = ~Salary + Percent_MBA + Percentile_ET, cex=0.6, data = placedET )