1 / 14

Chapter 16

Chapter 16. Integrating What You Have Learned: The General Linear Model. The Relationship Among Major Statistical Methods. The general linear model. Review of the Principles of Multiple Regression. Multiple correlation ( R ) Proportionate reduction in error ( R 2 ). The General Linear Model.

salaam
Download Presentation

Chapter 16

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 16 Integrating What You Have Learned: The General Linear Model

  2. The Relationship Among Major Statistical Methods • The general linear model

  3. Review of the Principles of Multiple Regression • Multiple correlation (R) • Proportionate reduction in error (R2)

  4. The General Linear Model • Actual value of Y • Error term (e) • The general linear model and multiple regression

  5. Bivariate Regression and Correlation as Special Cases of Multiple Regression • Bivariate regression • Special case of multiple regression • Bivariate correlation • Special case of multiple regression

  6. The t Test as a Special Case of ANOVA • t test • Two groups • ANOVA (F ratio) • More than two groups • Parallels in their basic logic • Numeric relationship of the procedures

  7. Links Between the t Test for Independent Means and ANOVA

  8. The t Test as a Special Case of the Significance Test for the Correlation Coefficient • Correlation coefficient • Degree of association between two variables • t test • Significance of the difference between the two population means • Both use the t distribution to determine significance

  9. The t Test as a Special Case of the Significance Test for the Correlation Coefficient • Group differences as associations among variables • Numerical predictor variables versus two-category nominal variable that divides the groups

  10. Relation Between Correlation and t Test for Independent Means

  11. ANOVA as a Special Case of the Significance Test of Multiple Regression • ANOVA for two groups as a special case of the significance of a bivariate correlation • ANOVA Correlation/Regression SSWithin = SSError SSTotal =SSTotal SSBetween = SSTotal – SSError R2 = r2

  12. ANOVA as a Special Case of the Significance Test of Multiple Regression • ANOVA for more than two groups as a special case of multiple correlation • Nominal coding

  13. Choice of Statistical Tests • t test, ANOVA, and correlation can all be done as multiple regression • However, each usually used in specific research contexts • Correlation and regression automatically give estimates of effect size and not just significance

  14. Controversies • What does causality mean? • Regularity theory of causality • Generative theory of causality

More Related