myData <- read.csv(paste("Data - Deans Dilemma.csv"))
placed <- myData[which(myData$Placement_B==1),]
males <- placed[which(placed$Gender=='M'),]
females <- placed[which(placed$Gender=='F'),]
head(females)## SlNo Gender Gender.B Percent_SSC Board_SSC Board_CBSE Board_ICSE
## 7 7 F 1 70 Others 0 0
## 10 10 F 1 59 CBSE 1 0
## 30 30 F 1 50 CBSE 1 0
## 31 31 F 1 74 ICSE 0 1
## 34 34 F 1 75 Others 0 0
## 35 35 F 1 60 CBSE 1 0
## Percent_HSC Board_HSC Stream_HSC Percent_Degree Course_Degree
## 7 54 Others Science 65 Others
## 10 74 CBSE Arts 59 Management
## 30 60 Others Science 71 Management
## 31 84 ISC Commerce 53 Commerce
## 34 77 Others Commerce 73 Management
## 35 72 CBSE Commerce 65 Management
## Degree_Engg Experience_Yrs Entrance_Test S.TEST Percentile_ET
## 7 0 2 None 0 0
## 10 0 1 None 0 0
## 30 0 0 MAT 1 62
## 31 0 0 MAT 1 68
## 34 0 0 MAT 1 48
## 35 0 1 MAT 1 72
## S.TEST.SCORE Percent_MBA Specialization_MBA Marks_Communication
## 7 0 59.80 Marketing & HR 63
## 10 0 63.83 Marketing & HR 50
## 30 62 65.04 Marketing & HR 55
## 31 68 68.63 Marketing & Finance 71
## 34 48 64.19 Marketing & HR 58
## 35 72 64.66 Marketing & Finance 57
## Marks_Projectwork Marks_BOCA Placement Placement_B Salary
## 7 56 50 Placed 1 260000
## 10 59 77 Placed 1 240000
## 30 61 59 Placed 1 180000
## 31 86 54 Placed 1 218000
## 34 57 80 Placed 1 250000
## 35 74 81 Placed 1 200000meanGender <- aggregate(placed$Salary, by=list(placed$Gender), FUN=mean)
meanGender## Group.1 x
## 1 F 253068.0
## 2 M 284241.9It is observed that on average females are getting lesser average pay than males.
H0: There is no difference between the average salary of male and female MBAs. H1: The average salary of the male MBAs is higher than the average salary of female MBAs. command used:t.test()
t.test(placed$Salary~placed$Gender)##
## Welch Two Sample t-test
##
## data: placed$Salary by placed$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 284241.9The value of p is: 0.00234
Since, p <0.05 Therefore, we reject the null hypothesis and conclude that, The average salary of male MBAs is higher than the Average salary of female MBAs