dean.df<-read.csv(paste("Data - Deans Dilemma.csv",sep=""))
  1. Submit your R code that creates a table showing the mean salary of males and females, who were placed.
tbl<-dean.df[which(dean.df$Placement_B==1),]
attach(tbl)
aggregate(Salary~Gender,data = tbl,FUN=mean)
##   Gender   Salary
## 1      F 253068.0
## 2      M 284241.9
  1. What is the average salary of male MBAs who were placed? From data above, 284241.9
  2. What is the average salary of female MBAs who were placed? From data above, 253068.0
  3. Submit R code to run a t-test for the Hypothesis “The average salary of the male MBAs is higher than the average salary of female MBAs.”
t.test(Salary~Gender,data=tbl)
## 
##  Welch Two Sample t-test
## 
## data:  Salary by Gender
## t = -3.0757, df = 243.03, p-value = 0.00234
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -51138.42 -11209.22
## sample estimates:
## mean in group F mean in group M 
##        253068.0        284241.9
  1. What is the p-value based on the t-test? The p-value is 0.00234
  2. Please interpret the meaning of the t-test, as applied to the average salaries of male and female MBAs. As p-value<0.05, we can say that the null hypothesis fails and that, “The average salary of the male MBAs is higher than the average salary of female MBAs.”