5220,8340,FEMALE,70,468,12,127 h. Fit a model using `sex`, and `exper` as explanatory variables. You might need to make an indicator variable for `sex`. Discuss your fit model, including an interpretation of all parameters in the model. i. What conclusions can be drawn about gender discrimination at Harris Trust based on your work above? Do these conclusions have to be qualified at all, or are they pretty clear cut? j. Add an interaction term to the model in h. Give an interpretation of the new model and give a graphic representation of the data and fit model.
<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
h. Fit a model using `sex`, and `exper` as explanatory variables. You might need to make an indicator variable for `sex`. Discuss your fit model, including an interpretation of all parameters in the model.
i. What conclusions can be drawn about gender discrimination at Harris Trust based on your work above? Do these conclusions have to be qualified at all, or are they pretty clear cut?
j. Add an interaction term to the model in h. Give an interpretation of the new model and give a graphic representation of the data and fit model.
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