REGRESSION

Table of Contents

1. Introduction
2. Definition of the Simple Linear Regression Model (LRM)
3. Derivation and Numerical Properties of OLS Estimates for the LRM
4. Statistical Properties of OLS Estimates Under LRM Assumptions
5. Confidence Intervals for Regression Coefficients
6. Hypothesis Tests for Regression Coefficients
7. Prediction using OLS
8. Analysis of Variance and Measure of Fit

Hot Link Index of Names Defined in regress

1. LRM |-->LRM
2. A0 |-->The nature of the data to be study with the LRM
3. A1 |-->The Population Regression Equation (PRE)
4. spec |-->Specification of the PRE
5. dlog |-->We
6. slog |-->is
7. A2 |-->Assumptions about Observed Terms
8. A3 |-->Assumption A3 about the LRM
9. A3* |-->Assumption A3*
10. A4 |-->Assumptions about the Unobserved Term $u$
11. A5 |-->Assumption A5
12. A6 |-->Assumption A6
13. A7 |-->Assumption A7
14. ols |-->The Least Squares Approach
15. yhat |-->Predicted value of $Y_i$:
16. err |-->Prediction error:
17. RSS |-->Sum of Squared Errors
18. b2hat |-->estimates
19. b1hat |-->as
20. normeq |-->normal equations
21. NP1 |-->Property 1
22. NP2 |-->Property 2
23. NP3 |-->Property 3
24. NP4 |-->Property 4
25. NP5 |-->Property 5
26. NP6 |-->Property 6
27. SP1 |-->1. Properties
28. SP2 |-->2. Properties Requiring Assumptions A0-A4 and
29. gmt |-->Gauss-Markov Theorem
30. SP3 |-->3. Properties Requiring Assumptions