# Regression Analysis for AIU jobsatisfaction data

First run a regression analysis using the BENEFITS column of all data points in the data set as the independent variable and the INTRINSIC job satisfaction column of all data points in the data set as the dependent variable. Create a graph with the trendline displayed. What is the least squares regression line equation? What are the slope and the y-intercept? What is the R-squared value?

Next, run a regression analysis using the BENEFITS column of all data points in the data set as the independent variable and the EXTRINSIC job satisfaction column of all data points in the data set as the dependent variable. Create a graph with the trendline displayed. What is the least squares regression line equation? What are the slope and the y-intercept? What is the R-squared value?

Next, run a regression analysis using the BENEFITS column of all data points in the data set as the independent variable and the OVERALL job satisfaction column of all data points in the data set as the dependent variable. Create a graph with the trendline displayed. What is the least squares regression line equation? What are the slope and the y-intercept? What is the R-squared value?

Finally, make very specific comments and give reasons regarding any similarities or differences in the output results. Which regression produces the strongest correlation coefficient result? Why?

GENDER AGE DEPT POSITION TENURE OVERALL INTRINSIC EXTRINSIC BENEFITS

1 3 3 1 1 4.7 4 4.1 5.2

1 1 1 1 3 4.5 4.2 4.7 6

1 3 1 2 2 6.5 4.2 6 4.6

1 3 3 1 2 4.2 4.3 5.6 5.3

1 1 3 1 2 6.4 3.2 5.5 4.5

1 1 3 1 1 6.6 4.5 4.4 4.2

1 2 2 2 1 4.5 4.7 4.4 5.2

1 1 1 1 2 6.1 4.9 6.9 5.9

1 2 3 1 2 5 4.9 4.6 5.6

1 3 2 2 3 4.2 5 6.2 5.5

1 2 1 1 1 4.1 5.5 5.5 4.1

1 3 1 2 2 5.1 5.6 4.9 4.7

1 2 1 1 2 6.5 5.6 5.5 4.9

1 1 2 2 2 6 5.7 4.6 3.6

1 1 3 1 1 4.7 5.7 5 4.9

2 3 1 1 1 6.7 5.9 6.1 5

2 1 3 1 2 4 6 4.7 5.7

2 2 1 1 2 4.6 6.2 4.6 4.6

2 1 1 1 2 6.2 6.5 6.1 5.7

2 3 3 1 1 4.3 6 4.4 4.6

2 2 3 1 1 4.5 6.2 6.5 5.4

2 2 1 1 3 5 6.3 6.2 5

2 3 2 2 1 5.4 4.2 4.7 4.6

2 1 3 2 2 6.9 4.4 5.5 4.7

2 2 2 2 3 4.3 4.6 4.6 4.4

KEY TO JOB SATISFACTION SURVEY

Gender

1 Male

2 Female

Age

1 21 and under

2 22-49

3 50 and over

Department

1 Human Resources

2 Information Technology

3 Administration

Position

1 Hourly Employee (Overtime Eligible)

2 Salaried Employee (No Overtime)

Tenure With Company

1 Less than 2 years

2 2 to 5 years

3 Over 5 Years

OVERALL Scale from 1-7

1 = Least Satisfied

7 = Most Satisfied

INTRINSIC Scale from 1-7

1= Least Satisfied

7= Most Satisfied

EXTRINSIC Scale from 1-7

1 = Least Satisfied

7 = Most Satisfied

BENEFITS Scale from 1-7

1= Least Satisfied

7= Most Satisfied

https://brainmass.com/statistics/regression-analysis/regression-analysis-for-aiu-jobsatisfaction-data-234901

#### Solution Summary

The solution provides step by step method for the calculation of Regression Analysis for AIU job satisfaction data . Formula for the calculation and Interpretations of the results are also included.