3-10 - 3-10 March 7, 2011 Thursday Simple Linear Regression...

Info iconThis preview shows page 1. Sign up to view the full content.

View Full Document Right Arrow Icon
This is the end of the preview. Sign up to access the rest of the document.

Unformatted text preview: 3-10 March 7, 2011 Thursday Simple Linear Regression μ YX= β0+ β1X εi ~ N( 0, σ2) μ YX= β0+ β1X yi= β0+ β1Xi+ εi yi= β0+ β1Xi 1. Var (εi) = σ2 Constant 2. 3. εi Normal εi's Independent 4. • Calibration (Inverse Prediction) y0= β0+ β1Xi 5. solve X0= y0- β0β1 6. 7. * Lack of Fit (display 8.9) 8. 9. Chapter 7. Page 191. The following: SE(xhat) = ( SE(muhat{Y | X}) ) / | Bhat 1| 10. 11. 12. 13. Lack of fit test: 14. For full and reduced model. 15. Chapter 8, page 217 16. 17. F Test, full & reduced model 18. (Change in SSE / change in Df SSE) / (MSE full ) u nder ANOVA table in JMP Output ) 19. 20. 21. (all of these values can be found ...
View Full Document

Ask a homework question - tutors are online