Dean’s Dilemma

1) Dean’s Dilemma Dataset

     dean1.df <- read.csv(paste("Data - Deans Dilemma.csv", sep=""))
      View(dean1.df)

2) Table Showing mean Salaries of males and females who were placed

      placed.df <- dean1.df[which(dean1.df$Placement_B=='1'),]
    aggregate(placed.df$Salary, by=list(gender=placed.df$Gender), mean)

##   gender        x
## 1      F 253068.0
## 2      M 284241.9

The average salary for Males is 284241.9 and for Females is 253068.
We see that there is a gender bias and that Males are paid a higher salary than females.

3) T-test

    attach(placed.df)
    t.test(Salary~Gender,data = placed.df)

## 
##  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

 The p value obtained is 0.00234
 
 Since the p value is not less than <0.001 we cannot reject our null hypothesis and the
 average salaries of male MBA is higher than average salary of female MBA.