1 / 8

10.4 – Inference as Decision

10.4 – Inference as Decision. Additional Notes. If you state parameter, you do not need to state hypotheses in words If not a random sample, you may not be able to generalize your results to the larger population.

Télécharger la présentation

10.4 – Inference as Decision

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. 10.4 – Inference as Decision

  2. Additional Notes • If you state parameter, you do not need to state hypotheses in words • If not a random sample, you may not be able to generalize your results to the larger population. • You do need to verify assumption that pop >10 x sample in order to use formula for standard deviation.

  3. Decisions • Choosing a fixed significance level, α, beforehand points to the outcome of the test as a decision. • If results are significant at level α, we reject Ho in favor of Ha. Otherwise we fail to reject Ho.

  4. Types of Error

  5. Probability of Type I Error • Type I error occurs when you reject Ho, but Ho is true. • The probability of this happening is equal to the significance level of the test, α.

  6. Probability of Type II Error • Type II error occurs when we accept Ho even though Ho is not true. The probability of this happening is the probability that the test statistic falls between your critical values.

  7. Power • The probability that a fixed level significance test will reject Ho when a particular alternative value (Ha) of the parameter is true. • The power of a test against any alternative is 1 minus the probability of a Type II error (β)for that alternative. • Power = 1- β

  8. Increasing the Power • Increase α • Consider a particular alternative that is farther away from μo. • Increase sample size • Decrease σ.

More Related