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- https://stats.libretexts.org/Courses/Luther_College/Psyc_350%3ABehavioral_Statistics_(Toussaint)/12%3A_Effect_SizeContributors and Attributions Online Statistics Education: A Multimedia Course of Study (http://onlinestatbook.com/). Project Leader: David M. Lane, Rice University.
- https://stats.libretexts.org/Bookshelves/Applied_Statistics/Business_Statistics_(OpenStax)/10%3A_Hypothesis_Testing_with_Two_Samples/10.08%3A_Chapter_ReviewThis page discusses methods for comparing two independent population means and proportions, addressing both known and unknown population standard deviations. It introduces Cohen's \(d\) as an effect s...This page discusses methods for comparing two independent population means and proportions, addressing both known and unknown population standard deviations. It introduces Cohen's \(d\) as an effect size measure and highlights the importance of equal variance assumptions. The text specifies distribution characteristics for various statistical tests, such as the Student's \(t\)-distribution and normal distribution based on data conditions.
- https://stats.libretexts.org/Bookshelves/Applied_Statistics/An_Introduction_to_Psychological_Statistics_(Foster_et_al.)/12%3A_Correlations/12.06%3A_Effect_SizeJust like \(η^2\) in ANOVA, \(r^2\) is interpreted as the amount of variance explained in the outcome variance, and the cut scores are the same as well: 0.01, 0.09, and 0.25 for small, medium, and lar...Just like \(η^2\) in ANOVA, \(r^2\) is interpreted as the amount of variance explained in the outcome variance, and the cut scores are the same as well: 0.01, 0.09, and 0.25 for small, medium, and large, respectively. Notice here that these are the same cutoffs we used for regular \(r\) effect sizes, but squared (0.102 = 0.01, 0.302 = 0.09, 0.502 = 0.25) because, again, the \(r^2\) effect size is just the squared correlation, so its interpretation should be, and is, the same.
- https://stats.libretexts.org/Courses/Rio_Hondo_College/PSY_190%3A_Statistics_for_the_Behavioral_Sciences/13%3A_Correlations/13.06%3A_Effect_SizeJust like \(η^2\) in ANOVA, \(r^2\) is interpreted as the amount of variance explained in the outcome variance, and the cut scores are the same as well: 0.01, 0.09, and 0.25 for small, medium, and lar...Just like \(η^2\) in ANOVA, \(r^2\) is interpreted as the amount of variance explained in the outcome variance, and the cut scores are the same as well: 0.01, 0.09, and 0.25 for small, medium, and large, respectively. Notice here that these are the same cutoffs we used for regular \(r\) effect sizes, but squared (0.102 = 0.01, 0.302 = 0.09, 0.502 = 0.25) because, again, the \(r^2\) effect size is just the squared correlation, so its interpretation should be, and is, the same.
- https://stats.libretexts.org/Courses/Sacramento_City_Colllege/PSYC_330%3A_Statistics_for_the_Behavioral_Sciences_with_Dr._DeSouza/14%3A_Correlations/14.06%3A_Effect_SizeJust like \(η^2\) in ANOVA, \(r^2\) is interpreted as the amount of variance explained in the outcome variance, and the cut scores are the same as well: 0.01, 0.09, and 0.25 for small, medium, and lar...Just like \(η^2\) in ANOVA, \(r^2\) is interpreted as the amount of variance explained in the outcome variance, and the cut scores are the same as well: 0.01, 0.09, and 0.25 for small, medium, and large, respectively. Notice here that these are the same cutoffs we used for regular \(r\) effect sizes, but squared (0.102 = 0.01, 0.302 = 0.09, 0.502 = 0.25) because, again, the \(r^2\) effect size is just the squared correlation, so its interpretation should be, and is, the same.
- https://stats.libretexts.org/Bookshelves/Introductory_Statistics/Introductory_Statistics_(Lane)/19%3A_Effect_Size
