A Dean’s Dilemma
TARANG JAIN
3 February 2018
R Markdown
This is an analysis of the Dean’s Dilemma case study.
Read the dataset using the read.csv() function.
dilemma.df <- read.csv(paste("Data - Deans Dilemma.csv" , sep = ""))
View(dilemma.df)Describing the Dataset
library(psych)
describe(dilemma.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 6994.72Summary statistics for important variables in the data set
summary(dilemma.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
## Calculate the median salary of all the students in the dataset.
median(dilemma.df$Salary)## [1] 240000Calculate the percentage of students who were placed upto 2 decimal places.
percent <- length(dilemma.df$Placement[dilemma.df$Placement == "Placed"]) / length(dilemma.df$Placement) * 100
options(digits = 4)
percent## [1] 79.8Create a dataframe called “placed”, that contains a subset of only those students who were successfully placed.
placed.df <- subset(dilemma.df , Placement == "Placed" , select = c(Percent_MBA , Gender , Salary))
placed.df## Percent_MBA Gender Salary
## 1 58.80 M 270000
## 2 66.28 M 200000
## 3 52.91 M 240000
## 4 57.80 M 250000
## 5 59.43 M 180000
## 6 56.81 M 300000
## 7 59.80 F 260000
## 8 57.23 M 235000
## 9 55.50 M 425000
## 10 63.83 F 240000
## 12 54.01 M 250000
## 13 51.58 M 180000
## 14 66.92 M 428000
## 15 58.21 M 450000
## 17 58.94 M 300000
## 18 54.78 M 240000
## 19 62.14 M 252000
## 21 63.26 M 280000
## 22 61.29 M 231000
## 23 62.51 M 224000
## 24 52.21 M 120000
## 25 60.85 M 260000
## 26 60.77 M 300000
## 27 51.75 M 120000
## 28 58.56 M 120000
## 29 63.70 M 250000
## 30 65.04 F 180000
## 31 68.63 F 218000
## 32 57.68 M 360000
## 33 54.96 M 150000
## 34 64.19 F 250000
## 35 64.66 F 200000
## 36 62.54 M 300000
## 37 52.41 M 330000
## 38 56.61 M 265000
## 39 61.83 M 340000
## 41 64.08 F 177600
## 44 77.89 M 236000
## 45 56.70 M 265000
## 46 57.74 M 200000
## 47 69.06 F 393000
## 48 68.81 F 360000
## 49 63.62 F 300000
## 50 53.42 M 250000
## 51 74.01 M 360000
## 52 65.33 F 180000
## 53 62.80 F 180000
## 54 58.53 M 270000
## 55 57.55 M 240000
## 56 60.76 M 300000
## 57 57.69 M 265000
## 58 64.15 M 350000
## 60 56.70 F 250000
## 61 58.32 F 180000
## 62 62.21 F 278000
## 63 57.61 M 150000
## 65 72.78 F 260000
## 66 62.77 M 180000
## 67 62.74 F 300000
## 69 68.85 M 400000
## 70 55.47 F 320000
## 71 56.86 F 240000
## 72 62.56 M 411000
## 73 66.72 F 287000
## 74 69.76 F 198000
## 76 62.90 M 300000
## 77 69.70 F 200000
## 78 66.53 F 180000
## 80 54.55 M 204000
## 81 62.46 M 250000
## 83 62.98 F 200000
## 84 62.27 M 275000
## 85 62.65 M 192000
## 86 57.83 F 240000
## 87 60.91 F 300000
## 90 71.04 M 450000
## 91 65.56 F 216000
## 92 52.71 M 220000
## 93 55.10 M 216000
## 95 67.31 M 300000
## 96 66.88 M 240000
## 97 63.59 M 360000
## 99 57.99 M 268000
## 101 56.66 M 265000
## 102 57.24 M 260000
## 103 67.53 M 240000
## 104 62.48 M 300000
## 105 59.69 F 240000
## 106 52.82 M 180000
## 107 64.75 M 240000
## 108 57.76 M 400000
## 110 52.43 M 180000
## 111 76.72 M 250000
## 113 69.35 F 295000
## 114 59.50 M 180000
## 115 62.89 F 300000
## 116 58.78 M 240000
## 117 57.10 M 120000
## 118 59.10 M 250000
## 119 58.46 M 275000
## 120 60.99 M 275000
## 121 59.24 F 150000
## 122 68.07 M 275000
## 123 60.03 M 300000
## 124 58.75 M 240000
## 125 69.81 M 336000
## 126 65.45 M 360000
## 127 62.40 M 280000
## 129 60.43 M 325000
## 130 60.76 M 204000
## 131 66.94 M 240000
## 132 68.53 M 240000
## 133 61.41 F 336000
## 134 59.75 M 218000
## 135 55.02 M 216000
## 136 67.20 M 336000
## 137 67.00 F 190000
## 138 64.27 F 230000
## 139 51.24 M 390000
## 140 57.65 M 500000
## 141 59.42 M 270000
## 142 67.99 F 150000
## 143 62.35 F 240000
## 145 62.01 F 276000
## 146 70.20 M 300000
## 147 60.44 M 168000
## 148 66.69 M 300000
## 150 59.81 M 270000
## 151 55.60 M 360000
## 152 62.00 M 300000
## 153 76.18 F 400000
## 154 57.03 M 220000
## 155 59.08 M 180000
## 156 58.85 M 180000
## 157 64.36 F 210000
## 158 62.36 F 210000
## 159 68.03 F 300000
## 160 66.86 F 290000
## 161 62.79 M 180000
## 163 59.47 F 230000
## 164 64.63 M 282000
## 165 53.57 M 260000
## 167 66.50 M 180000
## 168 54.97 M 260000
## 169 56.51 M 400000
## 170 62.16 M 420000
## 171 54.35 M 144000
## 172 64.44 F 300000
## 173 69.03 F 150000
## 174 57.31 F 220000
## 177 60.44 M 380000
## 178 59.99 M 290000
## 179 61.31 F 300000
## 180 55.42 F 252000
## 181 63.39 M 280000
## 182 65.83 M 240000
## 183 58.23 M 360000
## 185 65.69 M 180000
## 186 67.83 F 450000
## 187 73.52 M 200000
## 188 58.31 M 300000
## 189 53.37 M 350000
## 190 56.11 M 550000
## 192 63.36 M 250000
## 193 54.80 F 250000
## 195 53.94 M 250000
## 196 63.08 F 280000
## 197 55.01 M 250000
## 198 60.50 F 216000
## 199 52.42 M 204000
## 200 70.85 M 300000
## 201 67.05 M 240000
## 202 70.48 M 276000
## 203 64.34 M 940000
## 205 71.49 F 250000
## 206 59.99 M 300000
## 207 57.98 F 180000
## 208 71.00 F 236000
## 209 56.70 M 240000
## 210 61.26 M 250000
## 211 73.33 F 350000
## 212 59.50 M 210000
## 213 68.20 F 210000
## 214 58.40 F 250000
## 215 76.26 M 400000
## 216 70.71 M 300000
## 217 61.79 M 480000
## 218 68.55 M 250000
## 219 67.54 M 320000
## 221 69.94 M 385000
## 222 60.78 F 360000
## 223 53.49 M 300000
## 224 73.87 F 375000
## 225 60.98 M 250000
## 227 67.13 F 250000
## 228 58.73 F 275000
## 229 65.63 F 200000
## 230 61.58 F 150000
## 232 60.95 M 300000
## 233 60.41 M 225000
## 234 60.00 F 120000
## 235 71.77 F 250000
## 237 54.43 M 220000
## 238 57.24 M 265000
## 239 56.94 M 265000
## 242 61.29 M 260000
## 243 60.39 M 300000
## 244 51.73 M 180000
## 245 59.54 M 530000
## 246 56.75 M 156000
## 247 58.95 M 263000
## 249 63.23 M 400000
## 250 55.14 M 233000
## 251 62.28 M 300000
## 253 64.08 F 240000
## 254 58.54 M 180000
## 255 62.89 M 350000
## 256 55.67 M 198000
## 257 68.55 F 250000
## 259 61.30 M 690000
## 260 58.87 M 270000
## 261 65.25 F 240000
## 262 69.08 M 300000
## 263 62.48 M 340000
## 264 53.20 M 250000
## 265 59.84 M 390000
## 267 52.72 M 255000
## 268 55.03 M 300000
## 270 60.59 M 150000
## 271 72.29 M 300000
## 273 59.71 M 270000
## 274 53.47 F 240000
## 275 62.72 M 180000
## 276 66.06 M 285000
## 277 69.67 M 400000
## 278 66.46 M 500000
## 279 65.52 F 250000
## 280 56.78 M 300000
## 281 67.06 F 240000
## 282 71.86 M 300000
## 283 70.10 M 240000
## 286 52.38 M 240000
## 292 66.39 M 476000
## 293 66.04 M 290000
## 294 72.97 M 690000
## 295 52.64 M 300000
## 296 64.79 M 250000
## 297 59.32 F 162000
## 299 66.90 F 260000
## 300 66.23 M 500000
## 302 57.90 F 220000
## 303 58.67 M 270000
## 304 70.81 F 650000
## 305 68.07 M 350000
## 306 62.00 M 300000
## 308 56.60 M 265000
## 309 54.04 M 180000
## 311 64.28 F 300000
## 312 66.00 F 300000
## 313 68.68 F 300000
## 314 59.15 F 220000
## 316 54.12 M 240000
## 319 61.82 M 276000
## 320 66.28 M 250000
## 321 67.96 F 180000
## 323 71.43 F 252000
## 325 64.86 M 280000
## 327 66.63 F 350000
## 331 66.61 F 216000
## 333 61.01 M 264000
## 334 57.34 M 270000
## 335 56.63 F 300000
## 337 58.95 M 275000
## 339 54.50 M 300000
## 340 54.48 M 250000
## 341 69.71 F 260000
## 342 71.96 F 185000
## 343 63.91 F 216000
## 345 55.80 M 265000
## 346 52.81 M 300000
## 347 56.12 M 325000
## 348 53.37 M 267000
## 349 62.95 F 264000
## 351 60.11 M 240000
## 353 58.30 M 260000
## 354 69.12 F 240000
## 356 56.98 M 250000
## 357 63.42 F 180000
## 358 69.52 F 366000
## 359 67.69 F 210000
## 360 52.64 M 250000
## 361 56.81 M 250000
## 362 60.39 M 426000
## 363 60.04 M 270000
## 365 71.55 M 300000
## 366 56.45 M 132000
## 367 62.92 F 144000
## 368 55.40 M 220000
## 369 56.49 M 216000
## 370 74.49 M 400000
## 371 53.62 M 275000
## 372 69.72 M 295000
## 373 65.80 M 360000
## 374 60.23 F 204000
## 378 66.22 M 350000
## 380 77.30 F 300000
## 381 53.19 M 180000
## 385 61.00 M 252000
## 387 58.63 M 162000
## 388 59.50 M 450000
## 389 61.63 M 240000
## 390 70.17 F 300000Calculate median salary of students who were placed.
median(placed.df$Salary)## [1] 260000Create a table showing the mean salary of males and females, who were placed.
by(placed.df$Salary, placed.df$Gender, mean)## placed.df$Gender: F
## [1] 253068
## --------------------------------------------------------
## placed.df$Gender: M
## [1] 284242Generate a histogram showing a breakup of MBA performance of the students who were placed.
hist(placed.df$Percent_MBA,
main="MBA Performance of placed students",
xlab="MBA Percentage",
ylab="Count",
breaks=3,
col="red") 
Genereate a dataframe called “notplaced”, that contains a subset of only those students who were not placed after their MBA.
notplaced.df <- dilemma.df[ which(dilemma.df$Placement=='Not Placed') , ]
notplaced.df## SlNo Gender Gender.B Percent_SSC Board_SSC Board_CBSE Board_ICSE
## 11 11 F 1 79.60 Others 0 0
## 16 16 F 1 49.00 Others 0 0
## 20 20 M 0 66.00 Others 0 0
## 40 40 F 1 60.00 CBSE 1 0
## 42 42 F 1 40.00 CBSE 1 0
## 43 43 M 0 77.12 Others 0 0
## 59 59 M 0 70.00 CBSE 1 0
## 64 64 M 0 53.00 Others 0 0
## 68 68 M 0 54.00 CBSE 1 0
## 75 75 M 0 52.00 Others 0 0
## 79 79 F 1 78.89 Others 0 0
## 82 82 F 1 53.00 Others 0 0
## 88 88 M 0 75.00 Others 0 0
## 89 89 F 1 43.89 Others 0 0
## 94 94 M 0 40.50 Others 0 0
## 98 98 M 0 58.00 ICSE 0 1
## 100 100 F 1 50.00 CBSE 1 0
## 109 109 M 0 52.50 Others 0 0
## 112 112 F 1 44.00 CBSE 1 0
## 128 128 F 1 80.32 Others 0 0
## 144 144 F 1 61.00 Others 0 0
## 149 149 M 0 55.00 Others 0 0
## 162 162 M 0 54.16 ICSE 0 1
## 166 166 M 0 55.00 CBSE 1 0
## 175 175 M 0 59.00 ICSE 0 1
## 176 176 F 1 48.00 Others 0 0
## 184 184 M 0 64.00 ICSE 0 1
## 191 191 M 0 55.00 ICSE 0 1
## 194 194 M 0 56.00 Others 0 0
## 204 204 M 0 63.00 Others 0 0
## 220 220 M 0 70.00 CBSE 1 0
## 226 226 F 1 80.32 Others 0 0
## 231 231 F 1 64.00 Others 0 0
## 236 236 F 1 49.80 CBSE 1 0
## 240 240 M 0 74.00 CBSE 1 0
## 241 241 M 0 61.00 ICSE 0 1
## 248 248 M 0 55.00 Others 0 0
## 252 252 M 0 54.00 CBSE 1 0
## 258 258 M 0 54.07 Others 0 0
## 266 266 M 0 56.57 Others 0 0
## 269 269 M 0 75.00 Others 0 0
## 272 272 M 0 61.00 CBSE 1 0
## 284 284 F 1 68.30 ICSE 0 1
## 285 285 M 0 55.84 ICSE 0 1
## 287 287 M 0 75.90 Others 0 0
## 288 288 M 0 77.00 CBSE 1 0
## 289 289 F 1 51.00 CBSE 1 0
## 290 290 M 0 64.96 Others 0 0
## 291 291 F 1 71.40 Others 0 0
## 298 298 F 1 67.67 ICSE 0 1
## 301 301 M 0 68.00 Others 0 0
## 307 307 F 1 85.80 CBSE 1 0
## 310 310 M 0 67.00 ICSE 0 1
## 315 315 F 1 68.00 Others 0 0
## 317 317 M 0 57.00 Others 0 0
## 318 318 F 1 37.30 Others 0 0
## 322 322 F 1 61.28 Others 0 0
## 324 324 F 1 55.00 ICSE 0 1
## 326 326 M 0 66.80 Others 0 0
## 328 328 F 1 59.00 ICSE 0 1
## 329 329 M 0 65.00 ICSE 0 1
## 330 330 F 1 69.00 Others 0 0
## 332 332 M 0 63.68 Others 0 0
## 336 336 M 0 57.00 Others 0 0
## 338 338 M 0 56.00 ICSE 0 1
## 344 344 F 1 56.00 ICSE 0 1
## 350 350 M 0 59.20 CBSE 1 0
## 352 352 F 1 84.00 ICSE 0 1
## 355 355 M 0 56.00 Others 0 0
## 364 364 M 0 44.00 CBSE 1 0
## 375 375 F 1 52.00 Others 0 0
## 376 376 M 0 67.00 ICSE 0 1
## 377 377 M 0 46.00 CBSE 1 0
## 379 379 M 0 53.80 Others 0 0
## 382 382 M 0 67.00 Others 0 0
## 383 383 F 1 58.29 Others 0 0
## 384 384 M 0 61.00 Others 0 0
## 386 386 M 0 70.00 CBSE 1 0
## 391 391 M 0 74.00 Others 0 0
## Percent_HSC Board_HSC Stream_HSC Percent_Degree Course_Degree
## 11 87.00 ISC Commerce 72.35 Management
## 16 52.20 Others Commerce 85.00 Commerce
## 20 46.00 Others Commerce 65.00 Management
## 40 75.00 CBSE Commerce 68.00 Commerce
## 42 40.00 Others Commerce 51.00 Management
## 43 85.00 Others Commerce 56.77 Management
## 59 75.00 CBSE Commerce 60.00 Commerce
## 64 55.00 Others Commerce 42.00 Commerce
## 68 47.00 CBSE Commerce 59.00 Management
## 75 42.00 CBSE Science 69.00 Others
## 79 79.98 Others Science 71.60 Management
## 82 40.00 Others Arts 54.00 Arts
## 88 65.00 Others Science 59.00 Computer Applications
## 89 48.83 Others Commerce 55.00 Commerce
## 94 60.14 Others Commerce 52.37 Commerce
## 98 78.00 ISC Commerce 63.00 Commerce
## 100 69.00 CBSE Commerce 42.00 Arts
## 109 53.40 Others Commerce 55.21 Management
## 112 51.00 CBSE Commerce 45.00 Commerce
## 128 76.83 Others Commerce 76.30 Management
## 144 49.00 Others Science 63.00 Computer Applications
## 149 52.00 Others Commerce 54.20 Management
## 162 57.40 ISC Commerce 54.52 Management
## 166 70.00 CBSE Commerce 56.00 Commerce
## 175 90.00 Others Commerce 67.00 Computer Applications
## 176 62.00 Others Commerce 62.00 Management
## 184 69.00 Others Science 60.00 Engineering
## 191 68.00 Others Science 71.00 Science
## 194 59.00 Others Science 65.00 Science
## 204 43.00 Others Science 63.00 Management
## 220 73.00 Others Commerce 64.00 Management
## 226 55.00 Others Science 50.00 Engineering
## 231 68.00 Others Science 61.00 Engineering
## 236 51.20 CBSE Commerce 46.22 Commerce
## 240 69.00 CBSE Science 64.00 Management
## 241 50.00 ISC Science 62.00 Science
## 248 53.00 Others Arts 65.00 Management
## 252 59.20 CBSE Commerce 49.20 Commerce
## 258 70.33 Others Commerce 59.00 Commerce
## 266 82.66 Others Commerce 63.90 Commerce
## 269 68.00 Others Science 68.00 Computer Applications
## 272 52.00 Others Science 50.00 Commerce
## 284 86.33 Others Commerce 80.00 Management
## 285 54.00 ISC Arts 57.00 Management
## 287 70.00 Others Science 73.00 Engineering
## 288 69.20 CBSE Commerce 61.00 Commerce
## 289 56.00 CBSE Commerce 62.00 Commerce
## 290 45.16 Others Science 65.26 Computer Applications
## 291 75.20 Others Commerce 64.00 Management
## 298 75.00 Others Commerce 67.80 Commerce
## 301 67.00 Others Science 69.00 Engineering
## 307 69.00 CBSE Science 68.20 Engineering
## 310 65.33 Others Science 68.21 Engineering
## 315 48.00 Others Science 72.00 Computer Applications
## 317 73.00 Others Arts 59.00 Arts
## 318 44.40 Others Commerce 35.00 Commerce
## 322 70.83 Others Commerce 63.79 Management
## 324 69.00 ISC Commerce 65.00 Commerce
## 326 50.00 Others Commerce 56.38 Commerce
## 328 85.60 Others Commerce 75.20 Management
## 329 65.00 ISC Science 75.00 Computer Applications
## 330 78.20 CBSE Commerce 65.00 Management
## 332 58.19 Others Commerce 72.24 Commerce
## 336 60.00 Others Commerce 60.30 Management
## 338 58.00 ISC Commerce 67.00 Management
## 344 74.60 ISC Commerce 60.20 Commerce
## 350 68.00 Others Science 60.00 Management
## 352 87.00 ISC Commerce 75.00 Management
## 355 42.00 ISC Science 59.00 Computer Applications
## 364 45.00 CBSE Science 64.00 Management
## 375 52.80 Others Commerce 59.52 Management
## 376 63.00 Others Science 55.00 Management
## 377 54.00 Others Commerce 65.00 Management
## 379 46.30 Others Science 66.10 Management
## 382 76.00 Others Commerce 60.00 Management
## 383 55.00 Others Science 61.00 Management
## 384 53.00 Others Commerce 65.00 Management
## 386 55.00 Others Science 72.00 Management
## 391 85.00 Others Commerce 60.00 Commerce
## Degree_Engg Experience_Yrs Entrance_Test S.TEST Percentile_ET
## 11 0 0 K-MAT 1 98.69
## 16 0 0 MAT 1 74.28
## 20 0 0 PGCET 1 0.00
## 40 0 1 MAT 1 60.00
## 42 0 0 PGCET 1 49.00
## 43 0 0 CAT 1 35.00
## 59 0 0 MAT 1 77.00
## 64 0 0 None 0 0.00
## 68 0 0 MAT 1 64.00
## 75 0 0 MAT 1 63.00
## 79 0 0 MAT 1 68.00
## 82 0 1 MAT 1 65.00
## 88 0 1 None 0 0.00
## 89 0 2 MAT 1 71.20
## 94 0 1 MAT 1 42.26
## 98 0 0 None 0 0.00
## 100 0 0 None 0 0.00
## 109 0 1 None 0 0.00
## 112 0 0 None 0 0.00
## 128 0 0 MAT 1 47.31
## 144 0 0 K-MAT 1 43.50
## 149 0 0 CAT 1 20.00
## 162 0 1 MAT 1 22.95
## 166 0 0 MAT 1 72.00
## 175 0 0 MAT 1 50.00
## 176 0 1 MAT 1 56.39
## 184 1 0 MAT 1 85.00
## 191 0 1 MAT 1 86.00
## 194 0 2 MAT 1 60.00
## 204 0 0 MAT 1 73.00
## 220 0 0 MAT 1 84.00
## 226 1 0 PGCET 1 0.00
## 231 1 0 MAT 1 24.38
## 236 0 2 None 0 0.00
## 240 0 1 MAT 1 60.00
## 241 0 2 None 0 0.00
## 248 0 0 MAT 1 60.00
## 252 0 0 None 0 0.00
## 258 0 1 MAT 1 48.38
## 266 0 1 MAT 1 56.15
## 269 0 0 MAT 1 60.00
## 272 0 1 None 0 0.00
## 284 0 0 MAT 1 80.00
## 285 0 1 PGCET 1 0.00
## 287 1 1 MAT 1 58.10
## 288 0 0 None 0 0.00
## 289 0 1 MAT 1 60.00
## 290 0 1 MAT 1 54.48
## 291 0 0 MAT 1 58.06
## 298 0 0 MAT 1 49.94
## 301 1 0 MAT 1 87.50
## 307 1 0 MAT 1 75.50
## 310 1 0 MAT 1 63.00
## 315 0 0 None 0 0.00
## 317 0 1 MAT 1 75.00
## 318 0 0 None 0 0.00
## 322 0 0 MAT 1 60.00
## 324 0 0 MAT 1 55.00
## 326 0 1 MAT 1 57.00
## 328 0 0 MAT 1 95.65
## 329 0 0 K-MAT 1 93.00
## 330 0 0 MAT 1 50.00
## 332 0 0 MAT 1 36.56
## 336 0 0 MAT 1 59.00
## 338 0 0 None 0 0.00
## 344 0 2 None 0 0.00
## 350 0 1 MAT 1 79.00
## 352 0 0 CAT 1 80.00
## 355 0 2 None 0 0.00
## 364 0 0 MAT 1 97.00
## 375 0 0 MAT 1 33.91
## 376 0 0 MAT 1 89.00
## 377 0 0 MAT 1 71.32
## 379 0 0 MAT 1 30.71
## 382 0 0 MAT 1 48.38
## 383 0 0 K-MAT 1 71.00
## 384 0 0 MAT 1 46.47
## 386 0 0 CAT 1 50.00
## 391 0 0 MAT 1 58.89
## S.TEST.SCORE Percent_MBA Specialization_MBA Marks_Communication
## 11 98.69 69.78 Marketing & HR 71
## 16 74.28 53.29 Marketing & Finance 50
## 20 0.00 54.65 Marketing & Finance 53
## 40 60.00 67.28 Marketing & Finance 58
## 42 49.00 51.75 Marketing & Finance 50
## 43 35.00 56.34 Marketing & IB 56
## 59 77.00 51.29 Marketing & Finance 60
## 64 0.00 52.56 Marketing & Finance 50
## 68 64.00 51.45 Marketing & Finance 64
## 75 63.00 51.21 Marketing & Finance 51
## 79 68.00 71.63 Marketing & HR 71
## 82 65.00 56.11 Marketing & HR 54
## 88 0.00 56.19 Marketing & Finance 57
## 89 71.20 65.49 Marketing & HR 66
## 94 42.26 61.31 Marketing & Finance 56
## 98 0.00 60.29 Marketing & Finance 54
## 100 0.00 56.45 Marketing & HR 50
## 109 0.00 72.00 Marketing & Finance 73
## 112 0.00 54.76 Marketing & Finance 50
## 128 47.31 71.15 Marketing & Finance 74
## 144 43.50 67.13 Marketing & HR 59
## 149 20.00 55.83 Marketing & Finance 54
## 162 22.95 58.00 Marketing & Finance 55
## 166 72.00 55.41 Marketing & HR 59
## 175 50.00 59.47 Marketing & Finance 63
## 176 56.39 64.95 Marketing & HR 72
## 184 85.00 55.30 Marketing & HR 54
## 191 86.00 56.09 Marketing & HR 58
## 194 60.00 60.64 Marketing & HR 54
## 204 73.00 58.81 Marketing & IB 59
## 220 84.00 64.15 Marketing & Finance 52
## 226 0.00 62.29 Marketing & IB 67
## 231 24.38 62.83 Marketing & HR 57
## 236 0.00 57.32 Marketing & Finance 50
## 240 60.00 61.90 Marketing & HR 59
## 241 0.00 61.22 Marketing & HR 52
## 248 60.00 58.52 Marketing & Finance 54
## 252 0.00 52.32 Marketing & Finance 52
## 258 48.38 55.87 Marketing & HR 58
## 266 56.15 65.99 Marketing & HR 69
## 269 60.00 61.87 Marketing & Finance 61
## 272 0.00 65.13 Marketing & Finance 65
## 284 80.00 74.56 Marketing & Finance 71
## 285 0.00 54.99 Marketing & HR 50
## 287 58.10 75.71 Marketing & Finance 70
## 288 0.00 57.16 Marketing & HR 58
## 289 60.00 58.79 Marketing & HR 61
## 290 54.48 65.48 Marketing & HR 69
## 291 58.06 69.28 Marketing & HR 61
## 298 49.94 67.44 Marketing & Finance 72
## 301 87.50 60.69 Marketing & IB 61
## 307 75.50 72.14 Marketing & HR 74
## 310 63.00 60.02 Marketing & HR 76
## 315 0.00 63.83 Marketing & HR 58
## 317 75.00 59.81 Marketing & Finance 53
## 318 0.00 61.66 Marketing & Finance 62
## 322 60.00 57.29 Marketing & HR 54
## 324 55.00 62.93 Marketing & Finance 50
## 326 57.00 56.13 Marketing & Finance 50
## 328 95.65 66.94 Marketing & Finance 73
## 329 93.00 63.94 Marketing & HR 73
## 330 50.00 62.50 Marketing & Finance 65
## 332 36.56 66.18 Marketing & Finance 71
## 336 59.00 64.74 Marketing & Finance 67
## 338 0.00 65.28 Marketing & Finance 62
## 344 0.00 63.53 Marketing & Finance 65
## 350 79.00 58.44 Marketing & HR 52
## 352 80.00 72.21 Marketing & Finance 79
## 355 0.00 51.48 Marketing & Finance 50
## 364 97.00 53.39 Marketing & Finance 60
## 375 33.91 62.42 Marketing & Finance 68
## 376 89.00 60.22 Marketing & HR 66
## 377 71.32 52.36 Marketing & Finance 50
## 379 30.71 56.00 Marketing & Finance 53
## 382 48.38 50.83 Marketing & HR 54
## 383 71.00 56.81 Marketing & Finance 64
## 384 46.47 59.14 Marketing & HR 54
## 386 50.00 67.94 Marketing & Finance 77
## 391 58.89 60.36 Marketing & Finance 64
## Marks_Projectwork Marks_BOCA Placement Placement_B Salary
## 11 67 60 Not Placed 0 0
## 16 65 74 Not Placed 0 0
## 20 60 65 Not Placed 0 0
## 40 71 65 Not Placed 0 0
## 42 59 53 Not Placed 0 0
## 43 66 58 Not Placed 0 0
## 59 56 52 Not Placed 0 0
## 64 73 50 Not Placed 0 0
## 68 63 56 Not Placed 0 0
## 75 50 50 Not Placed 0 0
## 79 76 64 Not Placed 0 0
## 82 66 75 Not Placed 0 0
## 88 50 71 Not Placed 0 0
## 89 74 53 Not Placed 0 0
## 94 64 61 Not Placed 0 0
## 98 62 53 Not Placed 0 0
## 100 72 57 Not Placed 0 0
## 109 79 55 Not Placed 0 0
## 112 76 66 Not Placed 0 0
## 128 79 66 Not Placed 0 0
## 144 68 63 Not Placed 0 0
## 149 63 68 Not Placed 0 0
## 162 62 65 Not Placed 0 0
## 166 64 63 Not Placed 0 0
## 175 77 66 Not Placed 0 0
## 176 66 64 Not Placed 0 0
## 184 64 57 Not Placed 0 0
## 191 65 58 Not Placed 0 0
## 194 62 74 Not Placed 0 0
## 204 60 55 Not Placed 0 0
## 220 62 53 Not Placed 0 0
## 226 70 76 Not Placed 0 0
## 231 75 54 Not Placed 0 0
## 236 79 79 Not Placed 0 0
## 240 75 79 Not Placed 0 0
## 241 61 80 Not Placed 0 0
## 248 75 50 Not Placed 0 0
## 252 64 50 Not Placed 0 0
## 258 56 54 Not Placed 0 0
## 266 58 64 Not Placed 0 0
## 269 67 65 Not Placed 0 0
## 272 70 66 Not Placed 0 0
## 284 74 77 Not Placed 0 0
## 285 61 50 Not Placed 0 0
## 287 74 71 Not Placed 0 0
## 288 56 63 Not Placed 0 0
## 289 65 82 Not Placed 0 0
## 290 75 61 Not Placed 0 0
## 291 78 64 Not Placed 0 0
## 298 66 69 Not Placed 0 0
## 301 71 57 Not Placed 0 0
## 307 78 69 Not Placed 0 0
## 310 62 77 Not Placed 0 0
## 315 64 81 Not Placed 0 0
## 317 67 62 Not Placed 0 0
## 318 66 69 Not Placed 0 0
## 322 67 69 Not Placed 0 0
## 324 75 66 Not Placed 0 0
## 326 69 69 Not Placed 0 0
## 328 66 63 Not Placed 0 0
## 329 73 56 Not Placed 0 0
## 330 63 59 Not Placed 0 0
## 332 73 63 Not Placed 0 0
## 336 66 59 Not Placed 0 0
## 338 77 77 Not Placed 0 0
## 344 76 80 Not Placed 0 0
## 350 64 63 Not Placed 0 0
## 352 67 64 Not Placed 0 0
## 355 53 55 Not Placed 0 0
## 364 58 58 Not Placed 0 0
## 375 68 66 Not Placed 0 0
## 376 63 61 Not Placed 0 0
## 377 72 58 Not Placed 0 0
## 379 55 55 Not Placed 0 0
## 382 57 51 Not Placed 0 0
## 383 66 57 Not Placed 0 0
## 384 69 57 Not Placed 0 0
## 386 70 54 Not Placed 0 0
## 391 67 63 Not Placed 0 0Draw two histograms side-by-side, visually comparing the MBA performance of Placed and Not Placed students.
par(mfrow=c(1, 3))
hist(placed.df$Percent_MBA,
main="MBA Performance of placed students",
xlab="MBA Percentage",
ylab="Count",
breaks=3,
col="blue")
hist(notplaced.df$Percent_MBA,
main="MBA Performance of placed students",
xlab="MBA Percentage",
ylab="Count",
breaks=3,
col="blue")
par(mfrow=c(1, 1))
Draw two boxplots, one below the other, comparing the distribution of salaries of males and females who were placed.
library(lattice)
bwplot(Gender ~ Salary , data = placed.df , horizontal = TRUE , xlab = "Salary" , ylab = "Gender" , main = "Comparison of Salaries of Males and Females")
Create a dataframe called placedET, representing students who were placed after the MBA and who also gave some MBA entrance test before admission into the MBA program.
placedET.df <- subset(dilemma.df , Placement == "Placed" & S.TEST == 1 , select = c(Salary , Percent_MBA , Percentile_ET))
placedET.df## Salary Percent_MBA Percentile_ET
## 1 270000 58.80 55.00
## 2 200000 66.28 86.50
## 4 250000 57.80 75.00
## 5 180000 59.43 66.00
## 8 235000 57.23 43.12
## 9 425000 55.50 96.80
## 12 250000 54.01 79.00
## 13 180000 51.58 55.00
## 15 450000 58.21 33.00
## 19 252000 62.14 67.00
## 21 280000 63.26 70.00
## 22 231000 61.29 91.34
## 23 224000 62.51 35.00
## 24 120000 52.21 54.00
## 25 260000 60.85 62.00
## 26 300000 60.77 75.00
## 28 120000 58.56 49.00
## 29 250000 63.70 60.00
## 30 180000 65.04 62.00
## 31 218000 68.63 68.00
## 33 150000 54.96 76.00
## 34 250000 64.19 48.00
## 35 200000 64.66 72.00
## 36 300000 62.54 60.00
## 37 330000 52.41 79.00
## 38 265000 56.61 0.00
## 39 340000 61.83 70.00
## 41 177600 64.08 68.00
## 44 236000 77.89 50.48
## 45 265000 56.70 50.00
## 47 393000 69.06 95.00
## 48 360000 68.81 55.53
## 49 300000 63.62 92.00
## 51 360000 74.01 97.40
## 52 180000 65.33 76.00
## 53 180000 62.80 74.00
## 55 240000 57.55 94.00
## 56 300000 60.76 41.38
## 57 265000 57.69 68.00
## 58 350000 64.15 73.35
## 60 250000 56.70 52.00
## 61 180000 58.32 64.00
## 62 278000 62.21 50.89
## 63 150000 57.61 83.00
## 65 260000 72.78 88.00
## 66 180000 62.77 68.44
## 67 300000 62.74 71.00
## 69 400000 68.85 0.00
## 70 320000 55.47 58.00
## 71 240000 56.86 53.70
## 72 411000 62.56 93.00
## 73 287000 66.72 60.00
## 74 198000 69.76 65.00
## 76 300000 62.90 95.00
## 77 200000 69.70 89.00
## 78 180000 66.53 58.00
## 80 204000 54.55 78.00
## 81 250000 62.46 64.00
## 83 200000 62.98 65.00
## 84 275000 62.27 97.33
## 85 192000 62.65 67.00
## 87 300000 60.91 53.00
## 90 450000 71.04 87.00
## 91 216000 65.56 78.00
## 92 220000 52.71 71.00
## 95 300000 67.31 68.00
## 96 240000 66.88 68.00
## 97 360000 63.59 80.00
## 99 268000 57.99 74.00
## 101 265000 56.66 57.60
## 102 260000 57.24 60.00
## 104 300000 62.48 61.60
## 105 240000 59.69 59.00
## 107 240000 64.75 44.56
## 108 400000 57.76 13.00
## 111 250000 76.72 78.00
## 114 180000 59.50 68.50
## 116 240000 58.78 61.00
## 117 120000 57.10 89.69
## 119 275000 58.46 68.92
## 120 275000 60.99 68.71
## 121 150000 59.24 79.00
## 122 275000 68.07 70.00
## 124 240000 58.75 41.00
## 126 360000 65.45 89.00
## 127 280000 62.40 46.92
## 129 325000 60.43 50.00
## 130 204000 60.76 40.00
## 131 240000 66.94 95.00
## 132 240000 68.53 95.50
## 133 336000 61.41 96.00
## 134 218000 59.75 86.00
## 136 336000 67.20 84.27
## 137 190000 67.00 74.00
## 138 230000 64.27 61.00
## 139 390000 51.24 94.30
## 140 500000 57.65 69.00
## 141 270000 59.42 86.04
## 142 150000 67.99 75.00
## 143 240000 62.35 67.00
## 145 276000 62.01 40.00
## 146 300000 70.20 86.00
## 147 168000 60.44 82.00
## 148 300000 66.69 84.00
## 150 270000 59.81 0.00
## 152 300000 62.00 55.00
## 153 400000 76.18 78.74
## 154 220000 57.03 67.00
## 155 180000 59.08 75.00
## 156 180000 58.85 64.00
## 157 210000 64.36 58.00
## 158 210000 62.36 62.00
## 159 300000 68.03 92.00
## 160 290000 66.86 92.00
## 161 180000 62.79 67.00
## 163 230000 59.47 72.00
## 164 282000 64.63 47.41
## 165 260000 53.57 29.00
## 167 180000 66.50 56.39
## 168 260000 54.97 53.88
## 169 400000 56.51 79.00
## 170 420000 62.16 95.46
## 172 300000 64.44 66.00
## 173 150000 69.03 93.91
## 174 220000 57.31 70.00
## 177 380000 60.44 78.00
## 179 300000 61.31 57.50
## 180 252000 55.42 67.00
## 181 280000 63.39 58.00
## 182 240000 65.83 85.00
## 183 360000 58.23 55.00
## 185 180000 65.69 71.00
## 186 450000 67.83 95.00
## 187 200000 73.52 80.00
## 188 300000 58.31 84.00
## 193 250000 54.80 57.20
## 195 250000 53.94 58.00
## 196 280000 63.08 72.15
## 197 250000 55.01 53.70
## 198 216000 60.50 89.00
## 199 204000 52.42 39.00
## 200 300000 70.85 96.00
## 201 240000 67.05 80.00
## 202 276000 70.48 97.00
## 203 940000 64.34 82.66
## 205 250000 71.49 55.67
## 206 300000 59.99 85.00
## 207 180000 57.98 14.99
## 208 236000 71.00 80.40
## 209 240000 56.70 60.00
## 210 250000 61.26 64.00
## 211 350000 73.33 75.00
## 213 210000 68.20 70.00
## 214 250000 58.40 55.50
## 215 400000 76.26 81.20
## 216 300000 70.71 84.00
## 217 480000 61.79 86.00
## 218 250000 68.55 90.00
## 219 320000 67.54 89.95
## 221 385000 69.94 65.00
## 222 360000 60.78 80.00
## 223 300000 53.49 74.40
## 225 250000 60.98 65.00
## 227 250000 67.13 94.00
## 228 275000 58.73 43.00
## 229 200000 65.63 55.60
## 230 150000 61.58 78.00
## 232 300000 60.95 65.00
## 233 225000 60.41 56.00
## 235 250000 71.77 96.00
## 237 220000 54.43 58.00
## 239 265000 56.94 56.00
## 242 260000 61.29 60.00
## 243 300000 60.39 89.00
## 244 180000 51.73 39.00
## 245 530000 59.54 65.00
## 246 156000 56.75 66.60
## 247 263000 58.95 40.00
## 249 400000 63.23 72.00
## 250 233000 55.14 85.00
## 251 300000 62.28 83.00
## 253 240000 64.08 57.00
## 254 180000 58.54 64.25
## 256 198000 55.67 40.00
## 259 690000 61.30 56.00
## 260 270000 58.87 83.00
## 261 240000 65.25 98.00
## 263 340000 62.48 86.00
## 264 250000 53.20 70.00
## 267 255000 52.72 80.00
## 268 300000 55.03 93.40
## 270 150000 60.59 62.00
## 271 300000 72.29 75.00
## 273 270000 59.71 49.70
## 275 180000 62.72 57.63
## 276 285000 66.06 75.20
## 278 500000 66.46 75.00
## 279 250000 65.52 53.04
## 283 240000 70.10 88.00
## 286 240000 52.38 63.00
## 292 476000 66.39 80.00
## 293 290000 66.04 63.79
## 294 690000 72.97 95.50
## 295 300000 52.64 84.00
## 296 250000 64.79 49.00
## 297 162000 59.32 67.00
## 300 500000 66.23 64.00
## 302 220000 57.90 55.00
## 303 270000 58.67 76.20
## 304 650000 70.81 89.00
## 305 350000 68.07 73.00
## 306 300000 62.00 44.20
## 308 265000 56.60 57.00
## 309 180000 54.04 35.00
## 311 300000 64.28 62.00
## 313 300000 68.68 74.00
## 316 240000 54.12 0.00
## 319 276000 61.82 60.00
## 323 252000 71.43 82.00
## 325 280000 64.86 95.00
## 327 350000 66.63 60.00
## 333 264000 61.01 72.00
## 334 270000 57.34 93.40
## 335 300000 56.63 80.00
## 337 275000 58.95 84.00
## 339 300000 54.50 85.00
## 340 250000 54.48 78.00
## 341 260000 69.71 59.32
## 342 185000 71.96 88.00
## 343 216000 63.91 79.00
## 345 265000 55.80 73.00
## 346 300000 52.81 87.55
## 347 325000 56.12 84.00
## 348 267000 53.37 83.00
## 351 240000 60.11 61.28
## 353 260000 58.30 66.00
## 354 240000 69.12 63.00
## 356 250000 56.98 63.00
## 357 180000 63.42 60.00
## 359 210000 67.69 80.00
## 360 250000 52.64 48.00
## 361 250000 56.81 62.00
## 362 426000 60.39 26.53
## 363 270000 60.04 98.00
## 365 300000 71.55 88.56
## 366 132000 56.45 64.00
## 367 144000 62.92 92.66
## 369 216000 56.49 67.00
## 370 400000 74.49 91.00
## 371 275000 53.62 74.00
## 372 295000 69.72 59.00
## 373 360000 65.80 73.00
## 374 204000 60.23 70.00
## 378 350000 66.22 66.00
## 380 300000 77.30 96.16
## 381 180000 53.19 0.00
## 385 252000 61.00 0.00
## 387 162000 58.63 34.53
## 388 450000 59.50 50.53
## 389 240000 61.63 60.00
## 390 300000 70.17 77.00Draw a Scatter Plot Matrix for 3 variables - {Salary, Percent_MBA, Percentile_ET} using the dataframe placedET.
library(psych)
library(car)##
## Attaching package: 'car'## The following object is masked from 'package:psych':
##
## logitscatterplotMatrix(formula = ~ Salary + Percent_MBA + Percentile_ET, data = placedET.df)
Note that the echo = FALSE parameter was added to the code chunk to prevent printing of the R code that generated the plot.