1 / 1 / 1 / 1 / 1 / 5.4 / 3.3 / 5.5 / 4.5
1 / 1 / 2 / 1 / 3 / 3.2 / 3.9 / 6.2 / 5.5
1 / 1 / 1 / 1 / 1 / 5.5 / 4.2 / 5.9 / 4.6
1 / 2 / 1 / 1 / 1 / 5.2 / 4.5 / 6.1 / 6.4
1 / 2 / 1 / 1 / 3 / 5.9 / 4.7 / 5.5 / 4.8
1 / 1 / 1 / 2 / 3 / 4.9 / 2.5 / 4.7 / 6.2
1 / 2 / 2 / 2 / 3 / 5.8 / 3.4 / 5.5 / 4.7
1 / 2 / 2 / 2 / 2 / 5.5 / 3.6 / 5.6 / 6.6
1 / 1 / 3 / 2 / 2 / 5.1 / 3.8 / 6.8 / 5.8
1 / 1 / 1 / 2 / 1 / 2.6 / 4.1 / 5.5 / 4.1
1 / 2 / 1 / 2 / 1 / 4.4 / 4.2 / 3.3 / 4.6
1 / 1 / 1 / 2 / 1 / 2 / 4.3 / 5.6 / 5.3
1 / 2 / 3 / 2 / 1 / 2.5 / 4.7 / 4.4 / 5.2
2 / 3 / 3 / 1 / 2 / 5.4 / 3.2 / 4.7 / 3.6
2 / 2 / 2 / 1 / 3 / 3.3 / 3.6 / 4.6 / 4.4
2 / 2 / 3 / 1 / 1 / 3 / 3.9 / 3.2 / 5.7
2 / 3 / 3 / 1 / 2 / 2.3 / 4 / 2.4 / 4.6
2 / 2 / 3 / 1 / 2 / 3.7 / 4.4 / 4.9 / 4.8
2 / 3 / 2 / 1 / 2 / 6 / 4.5 / 2.6 / 3.5
2 / 2 / 3 / 2 / 1 / 5 / 2.8 / 4.6 / 6.3
2 / 3 / 2 / 2 / 1 / 4.8 / 3 / 3.1 / 5.2
2 / 3 / 2 / 2 / 1 / 5.5 / 3.6 / 6.1 / 4.7
2 / 3 / 3 / 2 / 2 / 5.1 / 3.6 / 4.8 / 4.7
2 / 1 / 3 / 2 / 1 / 5.1 / 3.7 / 3.9 / 3.4
2 / 1 / 3 / 2 / 1 / 5.6 / 3.8 / 3.4 / 4.2
2 / 2 / 3 / 2 / 1 / 3.5 / 4.2 / 6.5 / 5.4
2 / 1 / 3 / 2 / 3 / 4.8 / 4.3 / 6.2 / 2.9
2 / 3 / 3 / 2 / 3 / 5.4 / 4.5 / 5.4 / 4.8
2 / 3 / 1 / 2 / 3 / 5.7 / 4.8 / 6.1 / 4.9
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
Using Excel as your processing tool, work through three simple regression analyses.
1. First run a regression analysis using the BENEFITS column ofall data points in the AIU data set as the independent variable and the INTRINSIC job satisfaction column ofall data points in the AIU 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?
2. Next, run a regression analysis using the BENEFITS column ofall data points in the AIU data set as the independent variable and the EXTRINSIC job satisfaction column ofall data points in the AIU 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?
3. Next, run a regression analysis using the BENEFITS column ofall data points in the AIU data set as the independent variable and the OVERALL job satisfaction column ofall data points in the AIU 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?
4. 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?
1. Run a simple regression calculation in EXCEL using BENEFITS as the independent variable and INTRINSIC job satisfaction as the dependent variable using all29 data points from the AIU dataset.1.a. Give the graph of the trendline below:
(To do the regression and draw the scatter plot and trendline, the steps in EXCEL are as indicated on page 547(for Excel 2003), For Excel 2007, a tutorial can be found at the link shown at the link shown above.)
1.b. Provide the summary results of the regression copied and pasted below from your Excel output, as shown in the text. Do not submit Excel files.
1.c. State regression results below in mathematical form (i.e. in the form y=mx+b), and explain slope and y-intercept and their signs, and explain their meanings:
1.d. What is the R-squared value and its significance? / 1.a. Trendline -benefits/intrinsic regression
1.b. Summary results of regression from Excel
1.c. regression in equation form
y = -0.1342x + 4.5541
1.d. R-squared value/significance
R^2 = 0.043362
T-value = 0.043362*Sqrt((29-2)/(1-0.043362^2)) = 0.226
T-crit (one-tailed, a = 0.05, df = 29-2) = 1.70
0.226 < 1.70 NOT SiGNiFiCANT.
2. Run a simple regression calculation using BENEFITS as the independent variable and EXTRINSIC job satisfaction as the dependent variable using all29 data points from the AIU dataset.
2. a. Give the graph of the trendline below:
2.b. Provide the summary results of the regression copied and pasted below from your Excel output, as shown in the text. Do not submit Excel files.
2.c. State regression results below in mathematical form (i.e. in the form y=mx+b, and explain slope and y-intercept and their signs, and explain their meanings:
2.d. What is the R-squared value and its significance? / 2.a. Trendline-benefits/extrinsic regression
2.b. Summary results of regression from Excel
2.c. regression in equation form
y = 0.3123x + 3.4116
2.d. R-squared value/significance
R^2 = 0.054138
T-value = 0.054138*Sqrt((29-2)/(1-0.054138^2)) = 0.28
T-crit (one-tailed, a = 0.05, df = 29-2) = 1.70
0.28 < 1.70 NOT SiGNiFiCANT.
3. Run a simple regression calculation using BENEFITS as the independent variable and OVERALL job satisfaction as the dependent variable using all29 data points from the AIU dataset.
3.a.Give the graph of the trendline below:
3.b. Provide the summary results of the regression copied and pasted below from your Excel output, as shown in the text. Do not submit Excel files.
3.c. State regression results below in mathematical form (i.e. in the form y=mx+b, and explain slope and y-intercept and their signs, and explain their meanings:
3.d. What is the R-squared value and its significance? / 3.a. Trendline-benefits/overall regression
3.b. Summary results of regression from Excel
3.c. regression in equation form
y = -0.1545x + 5.312
3.d. R-squared value/significance
R^2 = 0.013165
T-value = 0.013165*Sqrt((29-2)/(1-0.013165^2)) = 0.068
T-crit (one-tailed, a = 0.05, df = 29-2) = 1.70
0.068 < 1.70 NOT SiGNiFiCANT.
4. a. Comment specifically on the similarities and differences in the output results.
4.b. Show formula used to calculate the correlation coefficient.
4.c. Identify which regression produced the strongest correlation coefficient.
4.d. Explain why it has the strongest correlation. / 4.a. similarities/differences:
4.b. correlation coefficient formula:
4.c. strongest correlation regression:
Benefits vs Extrinsic produced strongest correlation.
4.d. explanation:
It’s the only one that seems to have a positive effect on satisfaction.