- `bsal` = beginning salary (annual salary at time of hire) - `sal77` = annual salary in 1977 - `sex` = MALE or FEMALE - `senior` = months since hired - `age` = age in months - `educ` = years of education - `exper` = months of prior work experience banksalary.csv bsal,sal77,sex,senior,age,educ,exper 5040,12420,MALE,96,329,15,14 6300,12060,MALE,82,357,15,72 6000,15120,MALE,67,315,15,35.5 6000,16320.00098,MALE,97,354,12,24 6000,12300,MALE,66,351,12,56 6840,10380,MALE,92,374,15,41.5 8100,13979.99902,MALE,66,369,16,54.5 6000,10140,MALE,82,363,12,32 6000,12360,MALE,88,555,12,252 6900,10920,MALE,75,416,15,132 6900,10920,MALE,89,481,12,175 5400,12660.00098,MALE,91,331,15,17.5 6000,12960,MALE,66,355,15,64 6000,12360,MALE,86,348,15,25 5100,8940,FEMALE,95,640,15,165 4800,8580,FEMALE,98,774,12,381 5280,8760,FEMALE,98,557,8,190 5280,8040,FEMALE,88,745,8,90 4800,9000,FEMALE,77,505,12,63 4800,8820,FEMALE,76,482,12,6 5400,13320,FEMALE,86,329,15,24 5520,9600,FEMALE,82,558,12,97 5400,8940,FEMALE,88,338,12,26 5700,9000,FEMALE,76,667,12,90 3900,8760,FEMALE,98,327,12,0 4800,9780,FEMALE,75,619,12,144 6120,9360,FEMALE,78,624,12,208.5 5220,7860,FEMALE,70,671,8,102 5100,9660,FEMALE,66,554,8,96 4380,9600,FEMALE,92,305,8,6.25 4290,9180.000977,FEMALE,69,280,12,5 5400,9540,FEMALE,66,534,15,122 4380,10380,FEMALE,92,305,12,0 5400,8640,FEMALE,65,603,8,173 5400,11880,FEMALE,66,302,12,26 4500,12540.00098,FEMALE,96,366,8,52 5400,8400,FEMALE,70,628,12,82 5520,8880,FEMALE,67,694,12,196 5640,10080,FEMALE,90,368,12,55 4800,9240,FEMALE,73,590,12,228 5400,8640,FEMALE,66,771,8,228 4500,7980,FEMALE,80,298,12,8 5400,11940,FEMALE,77,325,12,38 5400,9420,FEMALE,72,589,15,49 6300,9780,FEMALE,66,394,12,86.5 5160,10680.00098,FEMALE,87,320,12,18 5100,11160,FEMALE,98,571,15,115 4800,8340,FEMALE,79,602,8,70 5400,9600,FEMALE,98,568,12,244 4020,9840,FEMALE,92,528,10,44 4980,8700,FEMALE,74,718,8,318 5280,9780,FEMALE,88,653,12,107 5700,8280,FEMALE,65,714,15,241 4800,8340,FEMALE,87,647,12,163 4800,13560,FEMALE,82,338,12,11 5700,10260,FEMALE,82,362,15,51 4380,9720,FEMALE,93,303,12,4.5 4380,10500.00098,FEMALE,89,310,12,0 5400,10680.00098,MALE,88,359,12,38 5400,11640,MALE,96,474,12,113 5100,7860,MALE,84,535,12,180 6600,11220,MALE,66,369,15,84 5100,8700,MALE,97,637,12,315 6600,12240.00098,MALE,83,536,15,215.5 5700,11220,MALE,94,392,15,36 6000,12180,MALE,91,364,12,49 6000,11580,MALE,83,521,15,108 6000,8940,MALE,80,686,12,272 6000,10680.00098,MALE,87,364,15,56 4620,11100,MALE,77,293,12,11.5 5220,10080,MALE,85,344,12,29 6600,15360.00098,MALE,83,340,15,64 5400,12600,MALE,78,305,12,7 6000,8940,MALE,78,659,8,320 5400,9480,MALE,88,690,15,359 6000,14400,MALE,96,402,16,45.5 5700,10620,FEMALE,88,410,15,61 5400,10320,FEMALE,78,584,15,51 4440,9600,FEMALE,97,341,15,75 6300,10860.00098,FEMALE,84,662,15,231 6000,9720,FEMALE,69,488,12,121 5100,9600,FEMALE,85,406,12,59 4800,11100,FEMALE,87,349,12,11 5100,10020.00098,FEMALE,87,508,16,123 5700,9780,FEMALE,74,542,12,116.5 5400,10440,FEMALE,72,604,12,169 5100,10560,FEMALE,84,458,12,36 4800,9240,FEMALE,84,571,16,214 6000,11940,FEMALE,86,486,15,78.5 4380,10020.00098,FEMALE,93,313,8,7.5 5580,7860,FEMALE,69,600,12,132.5 4620,9420,FEMALE,96,385,12,52 5220,8340,FEMALE,70,468,12,127 k. Often salary data is logged before analysis. Would you recommend logging starting salary in this study? Support your decision.

- `bsal` = beginning salary (annual salary at time of hire) - `sal77` = annual salary in 1977 - `sex` = MALE or FEMALE - `senior` = months since hired - `age` = age in months - `educ` = years of education - `exper` = months of prior work experience banksalary.csv bsal,sal77,sex,senior,age,educ,exper 5040,12420,MALE,96,329,15,14 6300,12060,MALE,82,357,15,72 6000,15120,MALE,67,315,15,35.5 6000,16320.00098,MALE,97,354,12,24 6000,12300,MALE,66,351,12,56 6840,10380,MALE,92,374,15,41.5 8100,13979.99902,MALE,66,369,16,54.5 6000,10140,MALE,82,363,12,32 6000,12360,MALE,88,555,12,252 6900,10920,MALE,75,416,15,132 6900,10920,MALE,89,481,12,175 5400,12660.00098,MALE,91,331,15,17.5 6000,12960,MALE,66,355,15,64 6000,12360,MALE,86,348,15,25 5100,8940,FEMALE,95,640,15,165 4800,8580,FEMALE,98,774,12,381 5280,8760,FEMALE,98,557,8,190 5280,8040,FEMALE,88,745,8,90 4800,9000,FEMALE,77,505,12,63 4800,8820,FEMALE,76,482,12,6 5400,13320,FEMALE,86,329,15,24 5520,9600,FEMALE,82,558,12,97 5400,8940,FEMALE,88,338,12,26 5700,9000,FEMALE,76,667,12,90 3900,8760,FEMALE,98,327,12,0 4800,9780,FEMALE,75,619,12,144 6120,9360,FEMALE,78,624,12,208.5 5220,7860,FEMALE,70,671,8,102 5100,9660,FEMALE,66,554,8,96 4380,9600,FEMALE,92,305,8,6.25 4290,9180.000977,FEMALE,69,280,12,5 5400,9540,FEMALE,66,534,15,122 4380,10380,FEMALE,92,305,12,0 5400,8640,FEMALE,65,603,8,173 5400,11880,FEMALE,66,302,12,26 4500,12540.00098,FEMALE,96,366,8,52 5400,8400,FEMALE,70,628,12,82 5520,8880,FEMALE,67,694,12,196 5640,10080,FEMALE,90,368,12,55 4800,9240,FEMALE,73,590,12,228 5400,8640,FEMALE,66,771,8,228 4500,7980,FEMALE,80,298,12,8 5400,11940,FEMALE,77,325,12,38 5400,9420,FEMALE,72,589,15,49 6300,9780,FEMALE,66,394,12,86.5 5160,10680.00098,FEMALE,87,320,12,18 5100,11160,FEMALE,98,571,15,115 4800,8340,FEMALE,79,602,8,70 5400,9600,FEMALE,98,568,12,244 4020,9840,FEMALE,92,528,10,44 4980,8700,FEMALE,74,718,8,318 5280,9780,FEMALE,88,653,12,107 5700,8280,FEMALE,65,714,15,241 4800,8340,FEMALE,87,647,12,163 4800,13560,FEMALE,82,338,12,11 5700,10260,FEMALE,82,362,15,51 4380,9720,FEMALE,93,303,12,4.5 4380,10500.00098,FEMALE,89,310,12,0 5400,10680.00098,MALE,88,359,12,38 5400,11640,MALE,96,474,12,113 5100,7860,MALE,84,535,12,180 6600,11220,MALE,66,369,15,84 5100,8700,MALE,97,637,12,315 6600,12240.00098,MALE,83,536,15,215.5 5700,11220,MALE,94,392,15,36 6000,12180,MALE,91,364,12,49 6000,11580,MALE,83,521,15,108 6000,8940,MALE,80,686,12,272 6000,10680.00098,MALE,87,364,15,56 4620,11100,MALE,77,293,12,11.5 5220,10080,MALE,85,344,12,29 6600,15360.00098,MALE,83,340,15,64 5400,12600,MALE,78,305,12,7 6000,8940,MALE,78,659,8,320 5400,9480,MALE,88,690,15,359 6000,14400,MALE,96,402,16,45.5 5700,10620,FEMALE,88,410,15,61 5400,10320,FEMALE,78,584,15,51 4440,9600,FEMALE,97,341,15,75 6300,10860.00098,FEMALE,84,662,15,231 6000,9720,FEMALE,69,488,12,121 5100,9600,FEMALE,85,406,12,59 4800,11100,FEMALE,87,349,12,11 5100,10020.00098,FEMALE,87,508,16,123 5700,9780,FEMALE,74,542,12,116.5 5400,10440,FEMALE,72,604,12,169 5100,10560,FEMALE,84,458,12,36 4800,9240,FEMALE,84,571,16,214 6000,11940,FEMALE,86,486,15,78.5 4380,10020.00098,FEMALE,93,313,8,7.5 5580,7860,FEMALE,69,600,12,132.5 4620,9420,FEMALE,96,385,12,52 5220,8340,FEMALE,70,468,12,127 k. Often salary data is logged before analysis. Would you recommend logging starting salary in this study? Support your decision.

Np Ms Office 365/Excel 2016 I Ntermed

1st Edition

ISBN:9781337508841

Author:Carey

Publisher:Carey

Chapter9: Working With Text Functions And Creating Custom Formats

Section: Chapter Questions

Problem 1.7CP

See similar textbooks

Related questions

Topic Video

Question

<ul>

- `bsal` = beginning salary (annual salary at time of hire)

- `sal77` = annual salary in 1977

- `sex` = MALE or FEMALE

- `senior` = months since hired

- `age` = age in months

- `educ` = years of education

- `exper` = months of prior work experience

</ul>

banksalary.csv

bsal,sal77,sex,senior,age,educ,exper

5040,12420,MALE,96,329,15,14

6300,12060,MALE,82,357,15,72

6000,15120,MALE,67,315,15,35.5

6000,16320.00098,MALE,97,354,12,24

6000,12300,MALE,66,351,12,56

6840,10380,MALE,92,374,15,41.5

8100,13979.99902,MALE,66,369,16,54.5

6000,10140,MALE,82,363,12,32

6000,12360,MALE,88,555,12,252

6900,10920,MALE,75,416,15,132

6900,10920,MALE,89,481,12,175

5400,12660.00098,MALE,91,331,15,17.5

6000,12960,MALE,66,355,15,64

6000,12360,MALE,86,348,15,25

5100,8940,FEMALE,95,640,15,165

4800,8580,FEMALE,98,774,12,381

5280,8760,FEMALE,98,557,8,190

5280,8040,FEMALE,88,745,8,90

4800,9000,FEMALE,77,505,12,63

4800,8820,FEMALE,76,482,12,6

5400,13320,FEMALE,86,329,15,24

5520,9600,FEMALE,82,558,12,97

5400,8940,FEMALE,88,338,12,26

5700,9000,FEMALE,76,667,12,90

3900,8760,FEMALE,98,327,12,0

4800,9780,FEMALE,75,619,12,144

6120,9360,FEMALE,78,624,12,208.5

5220,7860,FEMALE,70,671,8,102

5100,9660,FEMALE,66,554,8,96

4380,9600,FEMALE,92,305,8,6.25

4290,9180.000977,FEMALE,69,280,12,5

5400,9540,FEMALE,66,534,15,122

4380,10380,FEMALE,92,305,12,0

5400,8640,FEMALE,65,603,8,173

5400,11880,FEMALE,66,302,12,26

4500,12540.00098,FEMALE,96,366,8,52

5400,8400,FEMALE,70,628,12,82

5520,8880,FEMALE,67,694,12,196

5640,10080,FEMALE,90,368,12,55

4800,9240,FEMALE,73,590,12,228

5400,8640,FEMALE,66,771,8,228

4500,7980,FEMALE,80,298,12,8

5400,11940,FEMALE,77,325,12,38

5400,9420,FEMALE,72,589,15,49

6300,9780,FEMALE,66,394,12,86.5

5160,10680.00098,FEMALE,87,320,12,18

5100,11160,FEMALE,98,571,15,115

4800,8340,FEMALE,79,602,8,70

5400,9600,FEMALE,98,568,12,244

4020,9840,FEMALE,92,528,10,44

4980,8700,FEMALE,74,718,8,318

5280,9780,FEMALE,88,653,12,107

5700,8280,FEMALE,65,714,15,241

4800,8340,FEMALE,87,647,12,163

4800,13560,FEMALE,82,338,12,11

5700,10260,FEMALE,82,362,15,51

4380,9720,FEMALE,93,303,12,4.5

4380,10500.00098,FEMALE,89,310,12,0

5400,10680.00098,MALE,88,359,12,38

5400,11640,MALE,96,474,12,113

5100,7860,MALE,84,535,12,180

6600,11220,MALE,66,369,15,84

5100,8700,MALE,97,637,12,315

6600,12240.00098,MALE,83,536,15,215.5

5700,11220,MALE,94,392,15,36

6000,12180,MALE,91,364,12,49

6000,11580,MALE,83,521,15,108

6000,8940,MALE,80,686,12,272

6000,10680.00098,MALE,87,364,15,56

4620,11100,MALE,77,293,12,11.5

5220,10080,MALE,85,344,12,29

6600,15360.00098,MALE,83,340,15,64

5400,12600,MALE,78,305,12,7

6000,8940,MALE,78,659,8,320

5400,9480,MALE,88,690,15,359

6000,14400,MALE,96,402,16,45.5

5700,10620,FEMALE,88,410,15,61

5400,10320,FEMALE,78,584,15,51

4440,9600,FEMALE,97,341,15,75

6300,10860.00098,FEMALE,84,662,15,231

6000,9720,FEMALE,69,488,12,121

5100,9600,FEMALE,85,406,12,59

4800,11100,FEMALE,87,349,12,11

5100,10020.00098,FEMALE,87,508,16,123

5700,9780,FEMALE,74,542,12,116.5

5400,10440,FEMALE,72,604,12,169

5100,10560,FEMALE,84,458,12,36

4800,9240,FEMALE,84,571,16,214

6000,11940,FEMALE,86,486,15,78.5

4380,10020.00098,FEMALE,93,313,8,7.5

5580,7860,FEMALE,69,600,12,132.5

4620,9420,FEMALE,96,385,12,52

5220,8340,FEMALE,70,468,12,127

k. Often salary data is logged before analysis. Would you recommend logging starting salary in this study? Support your decision.

Expert Solution

Step by step

Solved in 2 steps

SEE SOLUTION Check out a sample Q&A here

Knowledge Booster

Learn more about

Need a deep-dive on the concept behind this application? Look no further. Learn more about this topic, computer-science and related others by exploring similar questions and additional content below.