Task 3a

Read the file Data -Deans Dilemma

setwd("C:/Users/Prabha Shankar/Desktop/Winter Internship/R file")
var1 <- read.csv(paste("Data - Deans Dilemma.csv"))
summary(var1)
##       SlNo       Gender     Gender.B       Percent_SSC     Board_SSC  
##  Min.   :  1.0   F:127   Min.   :0.0000   Min.   :37.00   CBSE  :113  
##  1st Qu.: 98.5   M:264   1st Qu.:0.0000   1st Qu.:56.00   ICSE  : 77  
##  Median :196.0           Median :0.0000   Median :64.50   Others:201  
##  Mean   :196.0           Mean   :0.3248   Mean   :64.65               
##  3rd Qu.:293.5           3rd Qu.:1.0000   3rd Qu.:74.00               
##  Max.   :391.0           Max.   :1.0000   Max.   :87.20               
##                                                                       
##    Board_CBSE      Board_ICSE      Percent_HSC    Board_HSC  
##  Min.   :0.000   Min.   :0.0000   Min.   :40.0   CBSE  : 96  
##  1st Qu.:0.000   1st Qu.:0.0000   1st Qu.:54.0   ISC   : 48  
##  Median :0.000   Median :0.0000   Median :63.0   Others:247  
##  Mean   :0.289   Mean   :0.1969   Mean   :63.8               
##  3rd Qu.:1.000   3rd Qu.:0.0000   3rd Qu.:72.0               
##  Max.   :1.000   Max.   :1.0000   Max.   :94.7               
##                                                              
##     Stream_HSC  Percent_Degree                Course_Degree
##  Arts    : 18   Min.   :35.00   Arts                 : 13  
##  Commerce:222   1st Qu.:57.52   Commerce             :117  
##  Science :151   Median :63.00   Computer Applications: 32  
##                 Mean   :62.98   Engineering          : 37  
##                 3rd Qu.:69.00   Management           :163  
##                 Max.   :89.00   Others               :  5  
##                                 Science              : 24  
##   Degree_Engg      Experience_Yrs   Entrance_Test     S.TEST      
##  Min.   :0.00000   Min.   :0.0000   MAT    :265   Min.   :0.0000  
##  1st Qu.:0.00000   1st Qu.:0.0000   None   : 67   1st Qu.:1.0000  
##  Median :0.00000   Median :0.0000   K-MAT  : 24   Median :1.0000  
##  Mean   :0.09463   Mean   :0.4783   CAT    : 22   Mean   :0.8286  
##  3rd Qu.:0.00000   3rd Qu.:1.0000   PGCET  :  8   3rd Qu.:1.0000  
##  Max.   :1.00000   Max.   :3.0000   GCET   :  2   Max.   :1.0000  
##                                     (Other):  3                   
##  Percentile_ET    S.TEST.SCORE    Percent_MBA   
##  Min.   : 0.00   Min.   : 0.00   Min.   :50.83  
##  1st Qu.:41.19   1st Qu.:41.19   1st Qu.:57.20  
##  Median :62.00   Median :62.00   Median :61.01  
##  Mean   :54.93   Mean   :54.93   Mean   :61.67  
##  3rd Qu.:78.00   3rd Qu.:78.00   3rd Qu.:66.02  
##  Max.   :98.69   Max.   :98.69   Max.   :77.89  
##                                                 
##            Specialization_MBA Marks_Communication Marks_Projectwork
##  Marketing & Finance:222      Min.   :50.00       Min.   :50.00    
##  Marketing & HR     :156      1st Qu.:53.00       1st Qu.:64.00    
##  Marketing & IB     : 13      Median :58.00       Median :69.00    
##                               Mean   :60.54       Mean   :68.36    
##                               3rd Qu.:67.00       3rd Qu.:74.00    
##                               Max.   :88.00       Max.   :87.00    
##                                                                    
##    Marks_BOCA         Placement    Placement_B        Salary      
##  Min.   :50.00   Not Placed: 79   Min.   :0.000   Min.   :     0  
##  1st Qu.:57.00   Placed    :312   1st Qu.:1.000   1st Qu.:172800  
##  Median :63.00                    Median :1.000   Median :240000  
##  Mean   :64.38                    Mean   :0.798   Mean   :219078  
##  3rd Qu.:72.50                    3rd Qu.:1.000   3rd Qu.:300000  
##  Max.   :96.00                    Max.   :1.000   Max.   :940000  
## 

Task 3b

Use R to create a table showing the average salary of maleas and females , who were placed .

var2 <-aggregate(var1$Salary , by = list(var1$Gender) ,FUN=mean)
var2
##   Group.1        x
## 1       F 193288.2
## 2       M 231484.8
boxplot(var1$Salary~var1$Gender , main="Avg Salary of males and females",ylab="Salary",xlab="Gender")

TAsk 3c

Use R to Run a t-test to test the following hypothesis : H1 : The average salary of the male is higher than the average salary of female MBAs.

Null Hypothesis : There is no significant difference between the salary of male nad female MBAs.

t.test(Salary~Gender , data=var1)
## 
##  Welch Two Sample t-test
## 
## data:  Salary by Gender
## t = -2.69, df = 278.55, p-value = 0.007577
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -66149.06 -10244.26
## sample estimates:
## mean in group F mean in group M 
##        193288.2        231484.8

value of p<0.01 , therfore the Null hypothesis is rejected .

Task 3d

2.Average salary of male MBAs who were placed : 231484.8 .

3.Average salary of female MBAs who were placed : 193288.2 .

4.the value of p on the t-test is : 0.007577.

5.Since the value of p is less than 0.01 , therfore our null hypothesis is wrong and we have accepted our alternative hypothesis .