part-2 for analysing Deans Dilemma using T-test Hypothisis
Survey publication Under guidance of Prof.Sameer Mathur(Ph.d) Associate Professor IIM-Lucknow
-----------------Case analysis----------------------
Using read.csv command to read the files
myfile.df <- read.csv(paste("Data - Deans Dilemma.csv", sep=""))
creating the data frame called “placed”
placed.df <- subset(myfile.df, Placement=='Placed')
View(placed.df)
Finding the average salary of male and female by using aggregate command.
mean <- aggregate(Salary ~ Gender, data=placed.df, mean)
mean
## Gender Salary
## 1 F 253068.0
## 2 M 284241.9
------Average salary of Male=28.42419%-------
------Average salary of female=25.30680%------
The average salary of the male MBAs is higher than the average salary of female MBAs.
t.test(Salary~Gender, data=placed.df, var.equal=TRUE)
##
## Two Sample t-test
##
## data: Salary by Gender
## t = -2.7597, df = 310, p-value = 0.00613
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## -53400.627 -8947.012
## sample estimates:
## mean in group F mean in group M
## 253068.0 284241.9
Find out the P-value based on T-test
##The p-value based on the t-test = 0.00613(p<0.05)
Please interpret the meaning of the t-test, as applied to the average salaries of male and female MBAs.
##Since we can conclude that the following statements states that p's value' "p-value<0.05" declared that null hypothesis "not holding any values then average salary of male MBAs is greater than that of female MBAs
Therefore we can conclude this survey Average salary of male MBAs is greater than that of female MBAs