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# Beta Technologies, Inc. Employee Salary Structure: regression analysis

I need help with estimate simple linear regression model for the management of Beta Technologies, Inc. is trying to determine the variable that best explains the variation of employee salaries using a simple of 52 full time employees in the attached file. I need to identify which of the following has the strongest linear relationship with annual salary.

Gender Age Prior_Experience Beta_Experience Education Annual_Salary
1 39 5 12 4 \$38,450
0 44 12 8 6 \$50,912
0 24 0 2 4 \$29,356
1 25 2 1 4 \$27,750
0 56 5 25 8 \$109,285
1 41 9 10 4 \$48,442
1 33 6 2 6 \$40,207
0 37 11 6 4 \$42,331
1 51 12 16 6 \$87,489
0 23 0 1 4 \$26,118
0 31 5 4 6 \$41,956
1 27 0 8 0 \$17,439
0 47 11 9 4 \$49,638
1 35 5 5 6 \$43,184
1 29 5 4 0 \$14,371
0 46 4 15 6 \$54,613
1 50 10 17 4 \$76,927
0 30 3 6 4 \$38,556
1 34 10 1 4 \$37,183
1 42 11 8 4 \$50,712
1 51 10 15 8 \$90,473
0 63 16 20 4 \$93,588
0 28 0 5 4 \$36,901
1 32 4 1 4 \$33,100
0 55 11 16 6 \$89,867
1 45 20 2 4 \$51,259
0 34 2 12 2 \$19,106
0 33 2 7 4 \$39,224
1 23 0 1 4 \$28,743
0 40 4 13 6 \$54,965
1 48 6 15 4 \$53,388
1 27 0 6 0 \$18,014
1 36 5 5 6 \$39,205
0 58 9 22 4 \$88,763
0 31 1 1 6 \$35,829
1 21 0 1 2 \$17,784
0 47 5 16 4 \$54,199
1 35 3 7 4 \$36,932
1 52 12 14 8 \$93,278
0 29 3 3 2 \$22,100
1 42 11 7 4 \$49,987
0 60 10 21 4 \$85,471
1 50 8 13 4 \$51,194
1 33 1 2 6 \$36,109
0 26 0 5 2 \$21,750
0 38 6 6 6 \$39,455
1 44 7 12 4 \$49,861
0 25 0 3 4 \$30,327
1 37 8 5 4 \$31,008
0 53 13 13 6 \$90,874
0 46 7 18 4 \$57,966
1 20 0 1 0 \$15,945

#### Solution Preview

Please find attached response to your question.

The regression analysis is present in the "Regression" Tab.

Results of multiple regression for Annual_Salary

Summary measures
Multiple R 0.9501
R-Square 0.9027