Effect Sizes and Power Analyses

Effect Sizes and Power Analyses

Nathaniel E. Helwig Assistant Professor of Psychology and Statistics

University of Minnesota (Twin Cities)

Updated 04-Jan-2017

Nathaniel E. Helwig (U of Minnesota)

Effect Sizes and Power Analyses

Updated 04-Jan-2017 : Slide 1

Copyright

Copyright ? 2017 by Nathaniel E. Helwig

Nathaniel E. Helwig (U of Minnesota)

Effect Sizes and Power Analyses

Updated 04-Jan-2017 : Slide 2

Outline of Notes

1) Effect Sizes: Definition and Overview Correlation ES Family Some Examples Difference ES Family Some Examples

2) Power Analyses: Definition and Overview One sample t test Two sample t test One-Way ANOVA Multiple regression

Nathaniel E. Helwig (U of Minnesota)

Effect Sizes and Power Analyses

Updated 04-Jan-2017 : Slide 3

Effect Sizes

Effect Sizes

Nathaniel E. Helwig (U of Minnesota)

Effect Sizes and Power Analyses

Updated 04-Jan-2017 : Slide 4

Effect Sizes Definition and Overview

What is an Effect Size?

An effect size (ES) measures the strength of some phenomenon: Correlation coefficient Regression slope coefficient Difference between means

ES are related to statistical tests, and are crucial for Power analyses (see later slides) Sample size planning (needed for grants) Meta-analyses (which combine ES from many studies)

Nathaniel E. Helwig (U of Minnesota)

Effect Sizes and Power Analyses

Updated 04-Jan-2017 : Slide 5

 ................
................

In order to avoid copyright disputes, this page is only a partial summary.

Google Online Preview   Download