Assembly-line work it is not suited for everybody because it is tedious and repetitive. A production manager would like to predict whether a newly hired worker will stay in the job for at least one year (Stay equals 1 if a new hire stays for at least one year, 0 otherwise). Predictor variables include age, gender (Female equals 1 if female, 0 otherwise), and whether the worker has worked on an assembly line before (Assembly equals 1 if worked before, 0 otherwise). The accompanying file includes data for 32 assembly-line workers. a-1. Estimate the linear probability model and the logistic regression model where being on the job one year later depends on Age, Female, and Assembly. Note: Negative values should be indicated by a minus sign. Round your answers to 2 decimal places. Predictor Variable Linear Model Logistic Model Constant _______ _________ Age ________ __________ Female _________ ___________ Assembly ________ ___________ Stay Age Female Assembly0 35 1 00 26 1 01 35 0 00 28 0 01 31 1 00 31 1 01 55 0 10 23 0 00 22 1 01 43 0 01 25 1 10 46 1 00 22 0 11 29 0 11 29 0 11 58 1 10 37 0 00 44 0 11 55 1 11 32 1 11 38 1 00 32 0 00 25 0 11 28 1 11 47 1 11 32 1 10 28 0 01 52 0 10 19 0 00 41 1 11 40 1 01 38 0 1
Assembly-line work it is not suited for everybody because it is tedious and repetitive. A production manager would like to predict whether a newly hired worker will stay in the job for at least one year (Stay equals 1 if a new hire stays for at least one year, 0 otherwise). Predictor variables include age, gender (Female equals 1 if female, 0 otherwise), and whether the worker has worked on an assembly line before (Assembly equals 1 if worked before, 0 otherwise). The accompanying file includes data for 32 assembly-line workers.
a-1. Estimate the linear probability model and the logistic regression model where being on the job one year later depends on Age, Female, and Assembly.
Note: Negative values should be indicated by a minus sign. Round your answers to 2 decimal places.
Predictor Variable Linear Model Logistic Model
Constant _______ _________
Age ________ __________
Female _________ ___________
Assembly ________ ___________
Stay Age Female Assembly
0 35 1 0
0 26 1 0
1 35 0 0
0 28 0 0
1 31 1 0
0 31 1 0
1 55 0 1
0 23 0 0
0 22 1 0
1 43 0 0
1 25 1 1
0 46 1 0
0 22 0 1
1 29 0 1
1 29 0 1
1 58 1 1
0 37 0 0
0 44 0 1
1 55 1 1
1 32 1 1
1 38 1 0
0 32 0 0
0 25 0 1
1 28 1 1
1 47 1 1
1 32 1 1
0 28 0 0
1 52 0 1
0 19 0 0
0 41 1 1
1 40 1 0
1 38 0 1
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