Dean Dilemma W2 D1

Dean Dilemma W2 D1

TASK 3b

setwd("/home/nimit")
deanDilemma<- read.csv("Data - Deans Dilemma.csv")
#View(deanDilemma)

placed<- deanDilemma[which(deanDilemma$Placement_B == 1),]  #Subset of placed student
aggregate(placed$Salary, by=list(placed$Gender), mean)  #Gender wise Average salary of placed student

##   Group.1        x
## 1       F 253068.0
## 2       M 284241.9

Average salary of male is higher than of female.

TASK 3c

H1: The average salary of the male MBAs is higher than the average salary of female MBAs.

t-test to test the hypothesis:

malePlaced<- placed[which(placed$Gender=='M'),]
femalePlaced<- placed[which(placed$Gender=='F'),]

t.test(malePlaced$Salary,femalePlaced$Salary)

## 
##  Welch Two Sample t-test
## 
## data:  malePlaced$Salary and femalePlaced$Salary
## 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 of x mean of y 
##  284241.9  253068.0

TASK 3d

1

Mean salary gender wise:

aggregate(placed$Salary, by=list(placed$Gender), mean)

##   Group.1        x
## 1       F 253068.0
## 2       M 284241.9

2

Average Salary of male who were placed:

mean(malePlaced$Salary)

## [1] 284241.9

3

Average Salary of female who were placed:

mean(femalePlaced$Salary)

## [1] 253068

4

t-test for the Hypothesis: The average salary of the male MBAs is higher than the average salary of female MBAs

t.test(malePlaced$Salary,femalePlaced$Salary)

## 
##  Welch Two Sample t-test
## 
## data:  malePlaced$Salary and femalePlaced$Salary
## 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 of x mean of y 
##  284241.9  253068.0

5

p-value = 0.00234

6

Interpret the result:

In placed MBA students, male have higher average salary than female. The t test showed there was a significant difference in average salary between male and female. ( p-value < 0.05 ).