1. Practical Statistics Regression

2. There are six statistics that will answer 90% of all questions! 1. Descriptive 2. Chi-square 3. Z-tests 4. Comparison of Means 5. Correlation 6. Regression

3. Regression tests the degree of association between interval and ratio measures, AND gives the best fit to the data.

4. Regression Does three things: 1. Association 2. Best fit 3. Prediction

5. Regression Regression creates an equation: A simple linear equation would be: Y = bX + a

6. An example from the classroom…. Can we use the correlations to create equations to estimate one variable from another?

7. For example: Evaluations = b(Personality) + a Y = bx + a

8. So… Evaluation = 0.637(Personality) - 0.530

9. An example can be found here: http://en.wikipedia.org/wiki/Linear_regression

12. The equations do not have to be linear?

14. Regression can use more than one variable to predict. This is called multiple regression. An example……

15. Caring = Evaluations But what is “Caring”??

17. But I know that this is not true!

18. Forced entry by significance….

19. Path Diagram

23. Service Encounter Are demographics related to satisfaction with a service encounter?

24. Service Encounter Are respondents’ personality traits related to satisfaction with a service encounter?

25. Service Encounter Are service providers’ personality traits related to satisfaction with a service encounter?