1 / 17

Chapter 14

Chapter 14. Chi-Square Tests. Chi-Square Tests. Hypothesis testing procedures for nominal variables (whose values are categories) Focus on the number of people in different categories. Chi-Square Statistic. Observed frequency distribution Expected frequency distribution

reyesb
Download Presentation

Chapter 14

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. Chapter 14 Chi-Square Tests

  2. Chi-Square Tests • Hypothesis testing procedures for nominal variables (whose values are categories) • Focus on the number of people in different categories

  3. Chi-Square Statistic • Observed frequency distribution • Expected frequency distribution • Chi-square statistic (χ2)

  4. Chi-Square Statistic • Chi-square distribution

  5. Chi-Square Statistic • Chi-square table

  6. The Chi-Square Test for Goodness of Fit • Levels of a single nominal variable

  7. The Chi-Square Test for Independence • Two nominal variables, each with several categories • Contingency table

  8. The Chi-Square Test for Independence • Independence • No relation between the variables in a contingency table • Sample and population

  9. The Chi-Square Test for Independence • Determining expected frequencies

  10. The Chi-Square Test for Independence • Figuring chi-square • Degrees of freedom

  11. Assumptions for Chi-Square Tests • No individual can be counted in more than one category or cell

  12. Effect Size for Chi-Square Test for Independence • 2 X 2 contingency table • Phi coefficient (φ) • small φ = .10 • medium φ = .30 • large φ = .50

  13. Effect Size for Chi-Square Test for Independence • Contingency tables larger than 2 x 2 • Cramer’s phi • Effect size for Cramer’s phi

  14. Power for Chi-Square Test for Independence (.05 significance level)

  15. Approximate Sample Size Needed for 80% Power (.05 significance level

  16. Controversies and Limitations • Minimum acceptable frequency for a category or cell • Small expected frequencies • At least 5 times as many individuals as categories (or cells) • Reduce power

  17. Chi-Square Tests in Research Articles • χ2(2, n = 101) = 11.89, p < .005

More Related