1 / 9

Means Tests

Hypothesis Testing. Assumptions Testing (Normality). Means Tests. Normality Tests. Many Statistical Tests require normal data You must verify normality with a test. Testing for Normality. How do we test for normality?

gauri
Télécharger la présentation

Means Tests

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. Hypothesis Testing Assumptions Testing (Normality) Means Tests

  2. Normality Tests Many Statistical Tests require normal data You must verify normality with a test

  3. Testing for Normality How do we test for normality? Compute the linear correlation coefficient between the sample data and normal scores

  4. Hypothesis Testing Normality Test H0: (null hypothesis): data normally distributed Ha: (alternative hypothesis): Data not normal

  5. Hypothesis Testing Normality Test Test Statistic P-value Critical Value (Alpha ɑ) = ??

  6. How to we use p? Compare p-value from test to specified significance level (alpha, α=0.05) If the p-value is less than or equal to α=0.05, reject the null hypothesis, Otherwise, do not reject (fail to) the null hypothesis

  7. Hypothesis Testing Normality Test P-value: <0.01 Alpha (ɑ) = 0.05 Since p is < ɑ Reject the null hypothesis

  8. Hypothesis Testing Normality Test Since we reject the null hypothesis H0: (null hypothesis): data normally distributed We accept the alternative hypothesis Ha: (alternative hypothesis): Data not normal …and determine that data are not normally distributed

More Related