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He argues that the standard deviation of the control group should not be influenced, at least in case of non-treatment control groups. If there are relevant differences in the standard deviations, Glass suggests not to use the pooled standard deviation but the standard deviation of the control group. In case, you want to do a pre-post comparison in single groups, calculator 4 or 5 should be more suitable, since they take the dependency in the data into account. The resulting effect size is called d Cohen and it represents the difference between the groups in terms of their common standard deviation. If the two groups have the same n, then the effect size is simply calculated by subtracting the means and dividing the result by the pooled standard deviation. Comparison of groups with equal size (Cohen's d and Glass Δ) Please click on the grey bars to show the calculators: 1. Here you will find a number of online calculators for the computation of different effect sizes and an interpretation table at the bottom of this page.
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The most popular effect size measure surely is Cohen's d (Cohen, 1988), but there are many more. In order to describe, if effects have a relevant magnitude, effect sizes are used to describe the strength of a phenomenon. in epidemiological studies or in large scale assessments, very small effects may reach statistical significance. If large data sets are at hand, as it is often the case f. Statistical significance mainly depends on the sample size, the quality of the data and the power of the statistical procedures. it may even describe a phenomenon that is not really perceivable in everyday life.
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But not every significant result refers to an effect with a high impact, resp. 1998, New Directions.Statistical significance specifies, if a result may not be the cause of random variations within the data. Prose selections edited and translated by Christopher Maurer.