1. Stat 200b. Chapter 8. Linear regression models.

2. n by 1, n by 2, 2 by 1, n by 1

4. 13 by 5

8. Effect of increasing seat height is 2  1

9. Some matrix review transpose multiplication inverse derivatives

10. Normal linear model. Estimation

11. Profile log likelihood

12. Straight-line/simple regression.

14. Fitted values. NB. Assuming matrix inverse exists

15. Weighted least squares. inverse existing

16. Example 8.8. Cycling data

19. Example 8.10. Maize data.

20. Likelihood quantities.

21. Take expected values

23. Normal distribution theory. Full rank case

24. A useful decomposition.

25. Confidence interval.

26. Gauss-Markov Theorem. page 374

27. There is a generalized inverse variant Example.

28. Eg. Teaching methods data, p. 427 Method average Usual 17 14 24 20 24 … 24 19.67 Praised 28 30 29 24 27 … 23 27.41