Dean’s Dilemma

Since MBA programs are prestigious in terms of the exposure the students get and placements, the deans of almost all B-schools come across the dilemma of setting qualitative as well as quantitative criteria to be followed to accept students. A lot of information regarding their academic, co-curricular performance and work experience is gathered to be able to select students. The following is a CSV format file which contains information like Gender, Percentage scored in 10th and 12th board examinations, Performance in under-grad, Work Experience, MBA Entrance Test taken, Performance in MBA, Salary post MBA. The analysis is given below:-

  1. Reading Data
setwd("C:/Users/Dell/Desktop/Project/Week 2/Day1/Task 3")
dilemma.df=read.csv("Data - Deans Dilemma.csv")
placed.df=dilemma.df[which(dilemma.df$Placement_B==1),]
  1. Creating a table showing the mean salary of males and females, who were placed
Avg_Age=aggregate(placed.df$Salary, by=list(Gender=placed.df$Gender), mean)
Avg_Age
##   Gender        x
## 1      F 253068.0
## 2      M 284241.9
  1. 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.B, data=placed.df)
## 
##  Welch Two Sample t-test
## 
## data:  Salary by Gender.B
## 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:
##  11209.22 51138.42
## sample estimates:
## mean in group 0 mean in group 1 
##        284241.9        253068.0

p-value, as we read from the t-test result, has come out to be 0.00234

  1. Interpret the meaning of the t-test, as applied to the average salaries of male and female MBAs

Based on the above output of the t-test, we cannot reject the hypothesis that the average salary of the male MBAs is higher than the average salary of female MBAs (p>0.001)