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
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