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Simple Regression Analyses

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Prepare a report using Excel as your processing tool to process three simple regression analyses.

1. 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.
2. 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.
3. 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.
4. Create a graph with the trendline displayed for each of the three different regressions. What are the least squares regression line equations for each of the three different regressions? What are the slopes and the y-intercepts? What are the R-squared values for the three different regressions? 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?

Here are the DATA SETS needed for this assignment.
GENDER AGE DEPT POSITION TENURE OVERALL INTRINSIC EXTRINSIC BENEFITS
1 3 3 1 1 3.8 5.5 4.1 6.1
1 1 1 2 3 5.3 4.2 4.7 6.3
1 2 1 2 1 6.5 5.3 3.8 5.1
1 2 2 1 2 4.6 4.3 5.6 5.3
1 1 3 2 3 6.4 4 5.5 4.5
1 1 3 1 2 5.1 4.5 4.4 5.5
1 2 2 2 3 5.3 4.7 3.1 5.2
1 1 2 1 1 3.7 5.3 6.9 5.1
1 2 3 1 1 5.5 4.9 4.6 5.6
1 2 2 2 3 4.2 3.4 6.2 5.5
1 2 2 1 1 5.2 5.5 5.5 4.1
2 3 2 1 1 5.1 6 4.9 5.2
2 2 1 1 2 6.5 6.2 3.2 5.3
2 2 2 2 2 6.5 4.2 4.6 6.2
2 2 3 1 1 5.9 5.7 5.7 5.4
2 2 1 1 1 6.8 6.4 6.1 4.2
2 1 2 1 3 5.1 3.7 3.9 3.2
2 2 2 2 2 4.6 6.2 4.6 6.2
2 1 2 1 2 6.2 6.5 5.5 5.7
2 3 2 1 1 5.6 6.2 4.4 5.6
2 2 3 2 1 4.5 6.2 4.4 5.4
2 2 1 2 3 5.9 6.3 6.2 4.3
2 1 2 1 3 5.4 5.7 4.7 5.7
2 1 3 1 2 6.9 5.2 5.5 6.3
2 2 2 2 1 5.6 4.6 3.3 5.6

KEY TO JOB SATISFACTION SURVEY
Gender
1 Male
2 Female
Age
1 16 - 21
2 22 - 49
3 50 - 65
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

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Solution Summary

The solution examines a simple regression analysis using Excel.

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Education
  • BSc , Wuhan Univ. China
  • MA, Shandong Univ.
Recent Feedback
  • "Your solution, looks excellent. I recognize things from previous chapters. I have seen the standard deviation formula you used to get 5.154. I do understand the Central Limit Theorem needs the sample size (n) to be greater than 30, we have 100. I do understand the sample mean(s) of the population will follow a normal distribution, and that CLT states the sample mean of population is the population (mean), we have 143.74. But when and WHY do we use the standard deviation formula where you got 5.154. WHEN & Why use standard deviation of the sample mean. I don't understand, why don't we simply use the "100" I understand that standard deviation is the square root of variance. I do understand that the variance is the square of the differences of each sample data value minus the mean. But somehow, why not use 100, why use standard deviation of sample mean? Please help explain."
  • "excellent work"
  • "Thank you so much for all of your help!!! I will be posting another assignment. Please let me know (once posted), if the credits I'm offering is enough or you ! Thanks again!"
  • "Thank you"
  • "Thank you very much for your valuable time and assistance!"
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