1. Guide to Using Excel For Basic Statistical Applications To Accompany Business Statistics: A Decision Making Approach, 7th Ed. Chapter 14: Introduction to Linear Regression and Correlation Analysis By Groebner, Shannon, Fry, & Smith Prentice-Hall Publishing Company Copyright, 2008

2. Chapter 14 Excel Examples Correlation Coefficient Correlation Coefficient Correlation Coefficient Correlation Coefficient Midwest Distribution Regression Analysis Regression Analysis Fitzpatrick and Associates Regression Analysis Regression Analysis Regression Analysis Regression Analysis Vantage Electronics Regression Analysis for Description Regression Analysis for Description Regression Analysis for Description Regression Analysis for Description Car Mileage

3. Chapter 14 Excel Examples Regression Analysis for Prediction Regression Analysis for Prediction Regression Analysis for Prediction Regression Analysis for Prediction Freedom Hospital Residual Analysis Residual Analysis Residual Analysis Residual Analysis Freedom Hospital

4. Correlation Analysis - Midwest Distribution Issue: The company wants to analyze the relationship between salary and years with the company. Objective: Use Excel to help test whether a significant linear relationship exists between salary and years with the company. Data file is Midwest.xls

5. Correlation Analysis – Midwest Distribution. Open the file Midwest.xls To construct the scatter diagram see the Personal Computers tutorial in Chapter 2.

6. Correlation Analysis – Midwest Distribution. Select the Data tab Select Data Analysis Select Correlation OK

7. Correlation Analysis – Midwest Distribution. Input Range = A1:B13 Grouped by Columns Labels in First Row New Worksheet Ply: Correlation

8. Correlation Analysis – Midwest Distribution. The correlation between Sales and Years with Midwest is 0.8325

9. Regression Analysis - Midwest Distribution Issue: The marketing manager wants to determine the relationship between sales and years with the company. Objective: Use Excel to test whether the apparent linear relationship is statistically significant. Data file is Midwest.xls

10. Regression Analysis – Midwest Distribution. Open the file Midwest.xls

11. Regression Analysis – Midwest Distribution. Select the Data tab Select Data Analysis Select Regression OK

12. Regression Analysis – Midwest Distribution. Input Y Range = A1:A13 Input X Range = B1:B13 Select Labels New Worksheet Ply: Correlation OK

13. Regression Analysis – Midwest Distribution. The output shows: the correlation coefficient the coefficients for the regression equation. for each additional year, the average increase in company sales is 49.91008 = $4,991

14. Regression Analysis - Fitzpatrick & Associates Issue: The Fitzpatrick analysts want to model the relationship between profits and number of employees. Objective: Use Excel to test whether the apparent linear relationship is statistically significant. Data file is Fortune 50.xls

15. Regression Analysis – Fitzpatrick & Associates Open the file Fortune50.xls

16. Regression Analysis – Fitzpatrick & Associates Because you want the Employees to plot on the horizontal axis, it needs to be to the left of Profit. To accomplish this, copy Column D to Column K. Select the Insert Tab Select Scatter chart Select the Scatter with only Markers

17. Regression Analysis – Fitzpatrick & Associates Add titles Delete Legend Move chart to new sheet titled Scatter plot

18. Regression Analysis – Fitzpatrick & Associates To find Regression: Return to the Data Sheet Select the Data tab Select Regression OK

19. Regression Analysis – Fitzpatrick & Associates Y Range = K3:K53 X Range = J3:J53 New Worksheet Ply OK

20. Regression Analysis – Fitzpatrick & Associates Output Shows R square and Coefficients

21. Regression Analysis for Vantage Electronics Issue: Analysts want to compare the effectiveness of the Vantage Sensor - Vanguard against its competitor, Scorpion. Objective: Use Excel to test whether the apparent linear relationship is statistically significant. Data file is Vanguard.xls

22. Regression Analysis for Vantage Electronics Using the procedures from this chapter Create a Scatter Plot Note: Copy the Scorpion data to the column to the right of the Vantage data. Add titles, delete legend, and move to a new sheet.

23. Regression Analysis for Vantage Electronics The resulting model will give you the regression coefficient and the slope

24. Regression Analysis for Description- Car Mileage Issue: Analysts want to determine the relationship between EPA highway mileage and automobile horsepower. Objective: Use Excel to test whether the apparent linear relationship is statistically significant. Data file is Automobiles.xls

25. Regression Analysis – Car Mileage Open the file Automobiles.xls Select the Data tab Select Data Analysis Select Regression OK

26. Regression Analysis – Car Mileage Input Y Range: B1:B31 Input X Range: F1:F31 Select Labels New Worksheet Ply: Auto OK

27. Regression Analysis – Car Mileage The output shows the coefficient of determination the coefficients for the regression equation.

28. Regression Analysis for Prediction - Freedom Hospital Issue: The administrator has been requested by the hospital’s board of directors to develop a model that can be used to predict the total charges for a geriatric patient. Objective: Use Excel to develop a statistically significant prediction model. Data file is Patients.xls

29. Regression Analysis for Prediction – Freedom Hospital Open the file Patients.xls Select the Data tab Select Data Analysis Select Regression OK

30. Regression Analysis for Prediction – Freedom Hospital Input Y Range: G1:G139 Input X Range: B1: B139 Select Labels New Worksheet Ply: Patients OK

31. Regression Analysis for Prediction – Freedom Hospital The Excel output shows the coefficient of determination and the coefficients of the linear regression model.

32. Issue: The administrators want to determine whether the prediction model developed is a valid use of regression analysis or whether it violates some of the necessary assumptions. Objective: Use Excel to analyze the residuals from the model. Data file is Patients.xls Residual Analysis - Freedom Hospital

33. Residual Analysis – Freedom Hospital In the Patients Data sheet: Select the Data tab Select Data Analysis Select Regression

34. Residual Analysis – Freedom Hospital Input Y Range: G1:G139 Input X Range: B1:B139 Select Labels Select Residuals Select Residual Plots OK

35. Residual Analysis – Freedom Hospital At the bottom of the regression output (note the row number) the residual for each observation is given.

36. Residual Analysis – Freedom Hospital The regression output will also plot the residuals.