Deans_Dilemma
Ashwin Prakash Nalwade
December 11, 2017
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dean.df <- read.csv(paste("Dean.csv"))
summary(dean.df)## 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
## 3a :
mediansalary <- median(dean.df$Salary)
mediansalary## [1] 2400003b :
prop.table(table(dean.df$Placement_B))##
## 0 1
## 0.202046 0.797954The percentage of students who were placed is 79.8%
3c :
require(dplyr)## Loading required package: dplyr##
## Attaching package: 'dplyr'## The following objects are masked from 'package:stats':
##
## filter, lag## The following objects are masked from 'package:base':
##
## intersect, setdiff, setequal, unionplaced <- filter(dean.df,Placement_B==1)
summary(placed)## SlNo Gender Gender.B Percent_SSC Board_SSC
## Min. : 1.00 F: 97 Min. :0.0000 Min. :37.00 CBSE : 94
## 1st Qu.: 92.75 M:215 1st Qu.:0.0000 1st Qu.:58.00 ICSE : 60
## Median :182.50 Median :0.0000 Median :65.92 Others:158
## Mean :186.45 Mean :0.3109 Mean :65.58
## 3rd Qu.:276.25 3rd Qu.:1.0000 3rd Qu.:74.45
## Max. :390.00 Max. :1.0000 Max. :87.20
##
## Board_CBSE Board_ICSE Percent_HSC Board_HSC
## Min. :0.0000 Min. :0.0000 Min. :41.0 CBSE : 81
## 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:55.0 ISC : 37
## Median :0.0000 Median :0.0000 Median :63.0 Others:194
## Mean :0.3013 Mean :0.1923 Mean :64.1
## 3rd Qu.:1.0000 3rd Qu.:0.0000 3rd Qu.:72.0
## Max. :1.0000 Max. :1.0000 Max. :94.7
##
## Stream_HSC Percent_Degree Course_Degree
## Arts : 14 Min. :35.50 Arts : 10
## Commerce:175 1st Qu.:57.61 Commerce : 94
## Science :123 Median :63.00 Computer Applications: 24
## Mean :63.22 Engineering : 30
## 3rd Qu.:69.00 Management :129
## Max. :89.00 Others : 4
## Science : 21
## Degree_Engg Experience_Yrs Entrance_Test S.TEST
## Min. :0.00000 Min. :0.0 MAT :214 Min. :0.0000
## 1st Qu.:0.00000 1st Qu.:0.0 None : 51 1st Qu.:1.0000
## Median :0.00000 Median :0.0 K-MAT : 20 Median :1.0000
## Mean :0.09615 Mean :0.5 CAT : 18 Mean :0.8365
## 3rd Qu.:0.00000 3rd Qu.:1.0 PGCET : 4 3rd Qu.:1.0000
## Max. :1.00000 Max. :3.0 GCET : 2 Max. :1.0000
## (Other): 3
## Percentile_ET S.TEST.SCORE Percent_MBA
## Min. : 0.00 Min. : 0.00 Min. :51.24
## 1st Qu.:47.29 1st Qu.:47.29 1st Qu.:57.64
## Median :65.00 Median :65.00 Median :61.30
## Mean :56.99 Mean :56.99 Mean :61.90
## 3rd Qu.:80.00 3rd Qu.:80.00 3rd Qu.:66.28
## Max. :98.00 Max. :98.00 Max. :77.89
##
## Specialization_MBA Marks_Communication Marks_Projectwork
## Marketing & Finance:177 Min. :50.00 Min. :50.00
## Marketing & HR :126 1st Qu.:53.00 1st Qu.:64.00
## Marketing & IB : 9 Median :58.00 Median :69.00
## Mean :60.59 Mean :68.74
## 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: 0 Min. :1 Min. :120000
## 1st Qu.:57.00 Placed :312 1st Qu.:1 1st Qu.:220000
## Median :63.00 Median :1 Median :260000
## Mean :64.71 Mean :1 Mean :274550
## 3rd Qu.:73.00 3rd Qu.:1 3rd Qu.:300000
## Max. :96.00 Max. :1 Max. :940000
## 3d :
medianplacedsalary <- median(placed$Salary)
medianplacedsalary## [1] 2600003e :
aggregate(placed$Salary,by=list(placed$Gender),mean)## Group.1 x
## 1 F 253068.0
## 2 M 284241.9Hence the mean Salary of male students is 284241.9,whereas that of female students is 253068.0
3f :
require(lattice)## Loading required package: latticehistogram(placed$Percent_MBA, main="MBA Performance of Placed Students", xlab = "MBA Percentage", col = "grey", type = "count", breaks=3)
3g :
notplaced <- filter(dean.df,Placement_B==0)
summary(notplaced)## SlNo Gender Gender.B Percent_SSC Board_SSC
## Min. : 11.0 F:30 Min. :0.0000 Min. :37.30 CBSE :19
## 1st Qu.:136.0 M:49 1st Qu.:0.0000 1st Qu.:54.03 ICSE :17
## Median :266.0 Median :0.0000 Median :59.20 Others:43
## Mean :233.7 Mean :0.3797 Mean :60.99
## 3rd Qu.:327.0 3rd Qu.:1.0000 3rd Qu.:68.00
## Max. :391.0 Max. :1.0000 Max. :85.80
##
## Board_CBSE Board_ICSE Percent_HSC Board_HSC
## Min. :0.0000 Min. :0.0000 Min. :40.00 CBSE :15
## 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:52.10 ISC :11
## Median :0.0000 Median :0.0000 Median :62.00 Others:53
## Mean :0.2405 Mean :0.2152 Mean :62.61
## 3rd Qu.:0.0000 3rd Qu.:0.0000 3rd Qu.:71.92
## Max. :1.0000 Max. :1.0000 Max. :90.00
##
## Stream_HSC Percent_Degree Course_Degree
## Arts : 4 Min. :35.00 Arts : 3
## Commerce:47 1st Qu.:58.00 Commerce :23
## Science :28 Median :63.00 Computer Applications: 8
## Mean :62.06 Engineering : 7
## 3rd Qu.:67.40 Management :34
## Max. :85.00 Others : 1
## Science : 3
## Degree_Engg Experience_Yrs Entrance_Test S.TEST
## Min. :0.00000 Min. :0.0000 MAT :51 Min. :0.0000
## 1st Qu.:0.00000 1st Qu.:0.0000 None :16 1st Qu.:1.0000
## Median :0.00000 Median :0.0000 CAT : 4 Median :1.0000
## Mean :0.08861 Mean :0.3924 K-MAT : 4 Mean :0.7975
## 3rd Qu.:0.00000 3rd Qu.:1.0000 PGCET : 4 3rd Qu.:1.0000
## Max. :1.00000 Max. :2.0000 G-MAT : 0 Max. :1.0000
## (Other): 0
## Percentile_ET S.TEST.SCORE Percent_MBA
## Min. : 0.00 Min. : 0.00 Min. :50.83
## 1st Qu.:21.48 1st Qu.:21.48 1st Qu.:56.10
## Median :56.15 Median :56.15 Median :60.29
## Mean :46.83 Mean :46.83 Mean :60.74
## 3rd Qu.:71.10 3rd Qu.:71.10 3rd Qu.:65.04
## Max. :98.69 Max. :98.69 Max. :75.71
##
## Specialization_MBA Marks_Communication Marks_Projectwork
## Marketing & Finance:45 Min. :50.00 Min. :50.00
## Marketing & HR :30 1st Qu.:54.00 1st Qu.:62.50
## Marketing & IB : 4 Median :59.00 Median :66.00
## Mean :60.35 Mean :66.86
## 3rd Qu.:66.50 3rd Qu.:73.00
## Max. :79.00 Max. :79.00
##
## Marks_BOCA Placement Placement_B Salary
## Min. :50.00 Not Placed:79 Min. :0 Min. :0
## 1st Qu.:56.50 Placed : 0 1st Qu.:0 1st Qu.:0
## Median :63.00 Median :0 Median :0
## Mean :63.06 Mean :0 Mean :0
## 3rd Qu.:68.50 3rd Qu.:0 3rd Qu.:0
## Max. :82.00 Max. :0 Max. :0
## 3h :
place <- histogram(placed$Percent_MBA, main="Placed", xlab = "MBA Percentage", col = "grey", type = "count", breaks=3)
notplace <- histogram(notplaced$Percent_MBA, main="not Placed", xlab = "MBA Percentage", col = "grey", type = "count", breaks=3)
print(place, split = c(1, 1, 2, 1), more = TRUE)
print(notplace, split = c(2, 1, 2, 1))
3i :
bwplot(Gender ~ Salary,data=placed,horizontal=TRUE,xlab ="Salary",ylab = "Gender",main ="Comparison of Salaries of Males and Females")
3j :
placedET <- filter(placed,S.TEST==1)
summary(placedET)## SlNo Gender Gender.B Percent_SSC Board_SSC
## Min. : 1.0 F: 80 Min. :0.0000 Min. :37.00 CBSE : 81
## 1st Qu.: 95.0 M:181 1st Qu.:0.0000 1st Qu.:58.00 ICSE : 50
## Median :183.0 Median :0.0000 Median :66.00 Others:130
## Mean :188.8 Mean :0.3065 Mean :65.80
## 3rd Qu.:276.0 3rd Qu.:1.0000 3rd Qu.:74.44
## Max. :390.0 Max. :1.0000 Max. :87.20
##
## Board_CBSE Board_ICSE Percent_HSC Board_HSC
## Min. :0.0000 Min. :0.0000 Min. :41.00 CBSE : 71
## 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:55.00 ISC : 31
## Median :0.0000 Median :0.0000 Median :63.00 Others:159
## Mean :0.3103 Mean :0.1916 Mean :64.03
## 3rd Qu.:1.0000 3rd Qu.:0.0000 3rd Qu.:72.00
## Max. :1.0000 Max. :1.0000 Max. :94.70
##
## Stream_HSC Percent_Degree Course_Degree
## Arts : 12 Min. :38.00 Arts : 8
## Commerce:145 1st Qu.:57.80 Commerce : 77
## Science :104 Median :63.00 Computer Applications: 23
## Mean :63.33 Engineering : 24
## 3rd Qu.:69.30 Management :109
## Max. :89.00 Others : 2
## Science : 18
## Degree_Engg Experience_Yrs Entrance_Test S.TEST
## Min. :0.00000 Min. :0.0000 MAT :214 Min. :1
## 1st Qu.:0.00000 1st Qu.:0.0000 K-MAT : 20 1st Qu.:1
## Median :0.00000 Median :0.0000 CAT : 18 Median :1
## Mean :0.09195 Mean :0.4904 PGCET : 4 Mean :1
## 3rd Qu.:0.00000 3rd Qu.:1.0000 GCET : 2 3rd Qu.:1
## Max. :1.00000 Max. :3.0000 G-MAT : 1 Max. :1
## (Other): 2
## Percentile_ET S.TEST.SCORE Percent_MBA
## Min. : 0.00 Min. : 0.00 Min. :51.24
## 1st Qu.:58.00 1st Qu.:58.00 1st Qu.:57.90
## Median :68.71 Median :68.71 Median :61.63
## Mean :68.12 Mean :68.12 Mean :62.09
## 3rd Qu.:83.00 3rd Qu.:83.00 3rd Qu.:66.22
## Max. :98.00 Max. :98.00 Max. :77.89
##
## Specialization_MBA Marks_Communication Marks_Projectwork
## Marketing & Finance:149 Min. :50.00 Min. :50.00
## Marketing & HR :104 1st Qu.:53.00 1st Qu.:64.00
## Marketing & IB : 8 Median :59.00 Median :70.00
## Mean :60.87 Mean :69.26
## 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: 0 Min. :1 Min. :120000
## 1st Qu.:57.00 Placed :261 1st Qu.:1 1st Qu.:220000
## Median :63.00 Median :1 Median :260000
## Mean :64.93 Mean :1 Mean :274861
## 3rd Qu.:73.00 3rd Qu.:1 3rd Qu.:300000
## Max. :96.00 Max. :1 Max. :940000
## 3k :
require(car)## Loading required package: car##
## Attaching package: 'car'## The following object is masked from 'package:dplyr':
##
## recodescatterplotMatrix(formula = ~ Salary + Percent_MBA + Percentile_ET, data=placedET)
Note that the echo = FALSE parameter was added to the code chunk to prevent printing of the R code that generated the plot.