1 / 6

P-value Approach for Test Conclusion

P-value Approach for Test Conclusion. Under the assumption that H 0 is true, the probability that the test statistic would take a value as extreme or more extreme than that actually observed is called the P -value of the test.

lila-hendrix
Download Presentation

P-value Approach for Test Conclusion

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. P-value Approach for Test Conclusion • Under the assumption that H0 is true, the probability that the test statistic would take a value as extreme or more extreme than that actually observed is called the P-value of the test. • Small P-value gives evidence against H0. Large P-value gives no evidence against H0. In general, the smaller the P-value the stronger the evidence against H0 provided by the data. • The decisive value of the P is the significance level . week 8

  2. Example week 8

  3. Decision Errors • When we perform a hypothesis test we hope that our decision will be correct, but sometimes it will be wrong. There are two possible errors that can be made in hypothesis test. • The error made by rejecting the null hypothesis H0 when in fact H0 is true is called a type I error. The probability of making a type I error is denoted by . • The error made by failing to reject the null hypothesis H0 when in fact H0 is false is called a type II error. The probability of making a type II error is denoted by . week 8

  4. Significance level and type I error The significance level  of any test is the P(Type I error). week 8

  5. Power • The probability of rejecting H0 when a particular alternative value of the parameter is true is called the power of the test to detect that alternative. • The power of a test against a particular alternative is Power = 1- β = 1- P( not rejecting H0 when H0 is false) = = P( rejecting H0 when H0 is false) week 8

  6. Example week 8

More Related