1 / 35

Econ 0160-W, Professor Berkowitz

Econ 0160-W, Professor Berkowitz. Lecture 2&3 (chapters 2 and 3) For course information click onto www.econ.pitt.edu , go to the faculty pages, click onto Daniel Berkowitz’s page and follow the links.

rasul
Download Presentation

Econ 0160-W, Professor Berkowitz

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Econ 0160-W, Professor Berkowitz • Lecture 2&3 (chapters 2 and 3) • For course information click onto www.econ.pitt.edu, go to the faculty pages, click onto Daniel Berkowitz’s page and follow the links. • For the next class, read over chapter 2, and do all of the problems in chapter 2 listed in problem set 1

  2. (a) The sampling distribution of

  3. The sampling distribution of , ctd.

  4. The sampling distribution of when Yis Bernoulli (p = .78):

  5. Things we want to know about the sampling distribution:

  6. The mean and variance of the sampling distribution of

  7. Mean and variance of sampling distribution of , ctd.

  8. The sampling distribution of when n is large

  9. The Law of Large Numbers:

  10. The Central Limit Theorem (CLT):

  11. Sampling distribution of when Y is Bernoulli, p = 0.78:

  12. Same example: sampling distribution of :

  13. Summary: The Sampling Distribution of

  14. (b) Why Use To Estimate Y?

  15. Why Use To Estimate Y?, ctd.

  16. Calculating the p-value, ctd.

  17. Calculating the p-value with Y known:

  18. Estimator of the variance of Y:

  19. Computing the p-value with estimated:

  20. What is the link between the p-value and the significance level?

  21. At this point, you might be wondering,...

  22. Comments on this recipe and the Student t-distribution

  23. Comments on Student t distribution, ctd.

  24. Comments on Student t distribution, ctd.

  25. Comments on Student t distribution, ctd.

  26. The Student-t distribution – summary

  27. Confidence intervals, ctd.

  28. Summary:

  29. Let’s go back to the original policy question:

More Related