dean.df<-read.csv(paste("Data - Deans Dilemma.csv",sep=""))
library('psych')
describe(dean.df)
## vars n mean sd median trimmed
## SlNo 1 391 196.00 113.02 196.00 196.00
## Gender* 2 391 1.68 0.47 2.00 1.72
## Gender.B 3 391 0.32 0.47 0.00 0.28
## Percent_SSC 4 391 64.65 10.96 64.50 64.76
## Board_SSC* 5 391 2.23 0.87 3.00 2.28
## Board_CBSE 6 391 0.29 0.45 0.00 0.24
## Board_ICSE 7 391 0.20 0.40 0.00 0.12
## Percent_HSC 8 391 63.80 11.42 63.00 63.34
## Board_HSC* 9 391 2.39 0.85 3.00 2.48
## Stream_HSC* 10 391 2.34 0.56 2.00 2.36
## Percent_Degree 11 391 62.98 8.92 63.00 62.91
## Course_Degree* 12 391 3.85 1.61 4.00 3.81
## Degree_Engg 13 391 0.09 0.29 0.00 0.00
## Experience_Yrs 14 391 0.48 0.67 0.00 0.36
## Entrance_Test* 15 391 5.85 1.35 6.00 6.08
## S.TEST 16 391 0.83 0.38 1.00 0.91
## Percentile_ET 17 391 54.93 31.17 62.00 56.87
## S.TEST.SCORE 18 391 54.93 31.17 62.00 56.87
## Percent_MBA 19 391 61.67 5.85 61.01 61.45
## Specialization_MBA* 20 391 1.47 0.56 1.00 1.42
## Marks_Communication 21 391 60.54 8.82 58.00 59.68
## Marks_Projectwork 22 391 68.36 7.15 69.00 68.60
## Marks_BOCA 23 391 64.38 9.58 63.00 64.08
## Placement* 24 391 1.80 0.40 2.00 1.87
## Placement_B 25 391 0.80 0.40 1.00 0.87
## Salary 26 391 219078.26 138311.65 240000.00 217011.50
## mad min max range skew kurtosis
## SlNo 145.29 1.00 391.00 390.00 0.00 -1.21
## Gender* 0.00 1.00 2.00 1.00 -0.75 -1.45
## Gender.B 0.00 0.00 1.00 1.00 0.75 -1.45
## Percent_SSC 12.60 37.00 87.20 50.20 -0.06 -0.72
## Board_SSC* 0.00 1.00 3.00 2.00 -0.45 -1.53
## Board_CBSE 0.00 0.00 1.00 1.00 0.93 -1.14
## Board_ICSE 0.00 0.00 1.00 1.00 1.52 0.31
## Percent_HSC 13.34 40.00 94.70 54.70 0.29 -0.67
## Board_HSC* 0.00 1.00 3.00 2.00 -0.83 -1.13
## Stream_HSC* 0.00 1.00 3.00 2.00 -0.12 -0.72
## Percent_Degree 8.90 35.00 89.00 54.00 0.05 0.24
## Course_Degree* 1.48 1.00 7.00 6.00 0.00 -1.08
## Degree_Engg 0.00 0.00 1.00 1.00 2.76 5.63
## Experience_Yrs 0.00 0.00 3.00 3.00 1.27 1.17
## Entrance_Test* 0.00 1.00 9.00 8.00 -2.52 7.04
## S.TEST 0.00 0.00 1.00 1.00 -1.74 1.02
## Percentile_ET 25.20 0.00 98.69 98.69 -0.74 -0.69
## S.TEST.SCORE 25.20 0.00 98.69 98.69 -0.74 -0.69
## Percent_MBA 6.39 50.83 77.89 27.06 0.34 -0.52
## Specialization_MBA* 0.00 1.00 3.00 2.00 0.70 -0.56
## Marks_Communication 8.90 50.00 88.00 38.00 0.74 -0.25
## Marks_Projectwork 7.41 50.00 87.00 37.00 -0.26 -0.27
## Marks_BOCA 11.86 50.00 96.00 46.00 0.29 -0.85
## Placement* 0.00 1.00 2.00 1.00 -1.48 0.19
## Placement_B 0.00 0.00 1.00 1.00 -1.48 0.19
## Salary 88956.00 0.00 940000.00 940000.00 0.24 1.74
## se
## SlNo 5.72
## Gender* 0.02
## Gender.B 0.02
## Percent_SSC 0.55
## Board_SSC* 0.04
## Board_CBSE 0.02
## Board_ICSE 0.02
## Percent_HSC 0.58
## Board_HSC* 0.04
## Stream_HSC* 0.03
## Percent_Degree 0.45
## Course_Degree* 0.08
## Degree_Engg 0.01
## Experience_Yrs 0.03
## Entrance_Test* 0.07
## S.TEST 0.02
## Percentile_ET 1.58
## S.TEST.SCORE 1.58
## Percent_MBA 0.30
## Specialization_MBA* 0.03
## Marks_Communication 0.45
## Marks_Projectwork 0.36
## Marks_BOCA 0.48
## Placement* 0.02
## Placement_B 0.02
## Salary 6994.72
placed <- placed <- dean.df[ which(dean.df$Placement=='Placed'), ]
describe(placed)
## vars n mean sd median trimmed
## SlNo 1 312 186.45 111.02 182.50 184.88
## Gender* 2 312 1.69 0.46 2.00 1.74
## Gender.B 3 312 0.31 0.46 0.00 0.26
## Percent_SSC 4 312 65.58 10.83 65.92 65.77
## Board_SSC* 5 312 2.21 0.88 3.00 2.26
## Board_CBSE 6 312 0.30 0.46 0.00 0.25
## Board_ICSE 7 312 0.19 0.39 0.00 0.12
## Percent_HSC 8 312 64.10 10.92 63.00 63.57
## Board_HSC* 9 312 2.36 0.87 3.00 2.45
## Stream_HSC* 10 312 2.35 0.56 2.00 2.37
## Percent_Degree 11 312 63.22 8.96 63.00 63.05
## Course_Degree* 12 312 3.87 1.62 4.00 3.81
## Degree_Engg 13 312 0.10 0.30 0.00 0.00
## Experience_Yrs 14 312 0.50 0.68 0.00 0.39
## Entrance_Test* 15 312 5.81 1.35 6.00 6.06
## S.TEST 16 312 0.84 0.37 1.00 0.92
## Percentile_ET 17 312 56.99 30.92 65.00 59.37
## S.TEST.SCORE 18 312 56.99 30.92 65.00 59.37
## Percent_MBA 19 312 61.90 5.77 61.30 61.70
## Specialization_MBA* 20 312 1.46 0.55 1.00 1.42
## Marks_Communication 21 312 60.59 8.99 58.00 59.65
## Marks_Projectwork 22 312 68.74 7.14 69.00 68.98
## Marks_BOCA 23 312 64.71 9.80 63.00 64.47
## Placement* 24 312 2.00 0.00 2.00 2.00
## Placement_B 25 312 1.00 0.00 1.00 1.00
## Salary 26 312 274550.00 93331.63 260000.00 263980.00
## mad min max range skew kurtosis
## SlNo 136.40 1.00 390.00 389.00 0.10 -1.14
## Gender* 0.00 1.00 2.00 1.00 -0.81 -1.34
## Gender.B 0.00 0.00 1.00 1.00 0.81 -1.34
## Percent_SSC 11.98 37.00 87.20 50.20 -0.12 -0.73
## Board_SSC* 0.00 1.00 3.00 2.00 -0.41 -1.58
## Board_CBSE 0.00 0.00 1.00 1.00 0.86 -1.26
## Board_ICSE 0.00 0.00 1.00 1.00 1.55 0.42
## Percent_HSC 13.34 41.00 94.70 53.70 0.36 -0.64
## Board_HSC* 0.00 1.00 3.00 2.00 -0.77 -1.24
## Stream_HSC* 0.00 1.00 3.00 2.00 -0.14 -0.75
## Percent_Degree 8.90 35.50 89.00 53.50 0.15 0.06
## Course_Degree* 1.48 1.00 7.00 6.00 0.01 -1.08
## Degree_Engg 0.00 0.00 1.00 1.00 2.73 5.45
## Experience_Yrs 0.00 0.00 3.00 3.00 1.25 1.24
## Entrance_Test* 0.00 1.00 9.00 8.00 -2.52 6.85
## S.TEST 0.00 0.00 1.00 1.00 -1.81 1.29
## Percentile_ET 22.24 0.00 98.00 98.00 -0.85 -0.50
## S.TEST.SCORE 22.24 0.00 98.00 98.00 -0.85 -0.50
## Percent_MBA 6.41 51.24 77.89 26.65 0.34 -0.51
## Specialization_MBA* 0.00 1.00 3.00 2.00 0.66 -0.66
## Marks_Communication 8.90 50.00 88.00 38.00 0.79 -0.16
## Marks_Projectwork 7.41 50.00 87.00 37.00 -0.28 -0.20
## Marks_BOCA 11.86 50.00 96.00 46.00 0.24 -0.91
## Placement* 0.00 2.00 2.00 0.00 NaN NaN
## Placement_B 0.00 1.00 1.00 0.00 NaN NaN
## Salary 59304.00 120000.00 940000.00 820000.00 2.26 10.34
## se
## SlNo 6.29
## Gender* 0.03
## Gender.B 0.03
## Percent_SSC 0.61
## Board_SSC* 0.05
## Board_CBSE 0.03
## Board_ICSE 0.02
## Percent_HSC 0.62
## Board_HSC* 0.05
## Stream_HSC* 0.03
## Percent_Degree 0.51
## Course_Degree* 0.09
## Degree_Engg 0.02
## Experience_Yrs 0.04
## Entrance_Test* 0.08
## S.TEST 0.02
## Percentile_ET 1.75
## S.TEST.SCORE 1.75
## Percent_MBA 0.33
## Specialization_MBA* 0.03
## Marks_Communication 0.51
## Marks_Projectwork 0.40
## Marks_BOCA 0.55
## Placement* 0.00
## Placement_B 0.00
## Salary 5283.86
table <-aggregate(dean.df$Salary~dean.df$Gender,data = dean.df,FUN=mean)
table
## dean.df$Gender dean.df$Salary
## 1 F 193288.2
## 2 M 231484.8
table[2,2]
## [1] 231484.8
table[1,2]
## [1] 193288.2
log.placed = log(placed$Salary)
t.test(log.placed~placed$Gender, var.equal = TRUE)
##
## Two Sample t-test
##
## data: log.placed by placed$Gender
## t = -2.8142, df = 310, p-value = 0.005203
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## -0.17482594 -0.03094897
## sample estimates:
## mean in group F mean in group M
## 12.40435 12.50723
P value is 0.005
Hypothesis is true