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Module 36: Correlation PitfallsEffect Size and Correlations

• Larger sample sizes require a smaller correlation coefficient to reach statistical significance – Therefore, a weak relationship can be perceived a statistically

significant because of a large sample

• It is necessary to make a judgment as to the practical importance of a significant correlation if there is a large sample size

• Categories for Correlation Coefficients – Small = .25 or less– Medium = .25 to .40– Large = .40 or more

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Restriction of Range

• Correlation coefficients can be biased if the full range of possible scores are not included in the sample

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Heterogeneity and Homogeneity

• Heterogeneity means that a sample contains a diverse range of score across possible subgroups

• Homogeneity indicates that participants are similar across subgroups that are potentially in the sample

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Common Variance

• Common variance is the proportion of variance that is shared across two variables

• A correlation coefficient is not a measure of common variance– r2 is a measure of common variance

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Correlation Does NOT Imply Causation

• Correlations do not imply causation

• A significant relationship between two variables does not indicate that variation in X causes variation in Y