1. Multiple Linear Regression Introduction to Business Statistics, 5e Kvanli/Guynes/Pavur (c)2000 South-Western College Publishing

2. The Multiple Regression Model Introduction to Business Statistics, 5e Kvanli/Guynes/Pavur (c)2000 South-Western College Publishing

3. Assumptions of the Multiple Regression Model The errors follow a normal distribution, centered at zero, with common variance The errors are independent Introduction to Business Statistics, 5e Kvanli/Guynes/Pavur (c)2000 South-Western College Publishing

4. Multiple Regression Model Assumptions Figure 15.3 Introduction to Business Statistics, 5e Kvanli/Guynes/Pavur (c)2000 South-Western College Publishing

5. Hypothesis Test for the Significance of the Model H o :  1 =  2 = … =  k H a : at least one of the  ’s  0 Reject H o if F > F ,k,n-k-1 Introduction to Business Statistics, 5e Kvanli/Guynes/Pavur (c)2000 South-Western College Publishing

6. F Statistic Figure 15.5 Introduction to Business Statistics, 5e Kvanli/Guynes/Pavur (c)2000 South-Western College Publishing

7. Test for H o :  i = 0 H o :  1 = 0 H a :  1  0 Reject H o if |t| > t ./2, n-k-1 Introduction to Business Statistics, 5e Kvanli/Guynes/Pavur (c)2000 South-Western College Publishing

8. (1-  ) 100% Confidence Interval for  i Introduction to Business Statistics, 5e Kvanli/Guynes/Pavur (c)2000 South-Western College Publishing

9. Coefficient of Determination R 2  SSR SST Introduction to Business Statistics, 5e Kvanli/Guynes/Pavur (c)2000 South-Western College Publishing

10. Curvilinear Models Introduction to Business Statistics, 5e Kvanli/Guynes/Pavur (c)2000 South-Western College Publishing

11. Curvilinear Models Figure 15.10 Introduction to Business Statistics, 5e Kvanli/Guynes/Pavur (c)2000 South-Western College Publishing

12. Extrapolation with Curvilinear Models Figure 15.12 Introduction to Business Statistics, 5e Kvanli/Guynes/Pavur (c)2000 South-Western College Publishing

13. Multicollinearity- VIF’s Introduction to Business Statistics, 5e Kvanli/Guynes/Pavur (c)2000 South-Western College Publishing

14. Dummy Variables The use of dummy or indicator variables in a regression analysis allows you to include qualitative variables in the model. For example: Introduction to Business Statistics, 5e Kvanli/Guynes/Pavur (c)2000 South-Western College Publishing

15. Stepwise Procedures Stepwise Procedures allow the evaluation of an additional variable in an established model. There are three methods: Forward Regression Backward Regression and Stepwise Regression Introduction to Business Statistics, 5e Kvanli/Guynes/Pavur (c)2000 South-Western College Publishing

16. Figure 15.18 Introduction to Business Statistics, 5e Kvanli/Guynes/Pavur (c)2000 South-Western College Publishing

17. (1-  ) 100% Confidence Interval for  y|x Introduction to Business Statistics, 5e Kvanli/Guynes/Pavur (c)2000 South-Western College Publishing

18. Prediction Interval for Y Xo Introduction to Business Statistics, 5e Kvanli/Guynes/Pavur (c)2000 South-Western College Publishing

19. Interaction Effects Introduction to Business Statistics, 5e Kvanli/Guynes/Pavur (c)2000 South-Western College Publishing

20. Interaction Effects Figure 15.23 Introduction to Business Statistics, 5e Kvanli/Guynes/Pavur (c)2000 South-Western College Publishing