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Chapter 7 Hypothesis Tests and Confidence Intervals in Multiple Regression.

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Presentation on theme: "Chapter 7 Hypothesis Tests and Confidence Intervals in Multiple Regression."— Presentation transcript:

1 Chapter 7 Hypothesis Tests and Confidence Intervals in Multiple Regression

2 2 Outline

3 3 Hypothesis Tests and Confidence Intervals for a Single Coefficient in Multiple Regression (SW Section 7.1)

4 4 Example: The California class size data

5 5 Standard errors in multiple regression in STATA

6 6 Tests of Joint Hypotheses (SW Section 7.2)

7 7 Tests of joint hypotheses, ctd.

8 8 Why can’t we just test the coefficients one at a time?

9 9 Suppose t 1 and t 2 are independent (for this calculation).

10 10

11 11 The F-statistic

12 12 The F-statistic testing  1 and  2 :

13 13 Large-sample distribution of the F-statistic

14 14

15 15 Computing the p-value using the F-statistic:

16 16 F-test example, California class size data:

17 17

18 18 The “restricted” and “unrestricted” regressions

19 19 Simple formula for the homoskedasticity-only F-statistic:

20 20 Example:

21 21 The homoskedasticity-only F-statistic – summary

22 22 Digression: The F distribution

23 23 The F q,n–k–1 distribution:

24 24 Another digression: A little history of statistics…

25 25 A little history of statistics, ctd…

26 26 Summary: the homoskedasticity-only F- statistic and the F distribution

27 27 Summary: testing joint hypotheses

28 28 Testing Single Restrictions on Multiple Coefficients (SW Section 7.3)

29 29 Testing single restrictions on multiple coefficients, ctd.

30 30 Method 1: Rearrange (“transform”) the regression

31 31 Rearrange the regression, ctd.

32 32 Method 2: Perform the test directly

33 33 Confidence Sets for Multiple Coefficients (SW Section 7.4)

34 34 Joint confidence sets ctd.

35 35

36 36 Confidence set based on inverting the F-statistic

37 37 An example of a multiple regression analysis – and how to decide which variables to include in a regression…

38 38 A general approach to variable selection and “model specification”

39 39 Digression about measures of fit…

40 40 Back to the test score application:

41 41 More California data…

42 42 Digression on presentation of regression results

43 43

44 44 Summary: Multiple Regression


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