2022 Introduction to Statistics in Research Mitchell 2nd ed

I N T R O T O R E S E A R C H : D A T A V I S U A L I Z A T I O N & C O M M O N S T A T T E S T S

EFFECT SIZE

The effect size tells us that the significance is not due to chance. Essentially, it indicates how strong of an observed effect and is quite helpful in additional studies. In the independent sample t-test, SPSS Version 27 will provide three different effect size tests: Cohen’s d, Hedges’ correction, and Glass’s delta. Cohen’s d standardizes the mean difference and has broken the effect into ranges: small effect = 0.20, medium effect = 0.50, and large effect = 0.80

For independent- samples t test, Adams & McGuire recommend either Cohen’s d or r pb which means (point-biserial correlation).

Effect size test

When to use

Cohen’s d

Two groups have similar SDs and the same size sample Different and/or small sample size (i.e. 20 males in group 1 and 10 females in group 2) Small sample size means less than 20. If each group has a different SD. It is also used between the experimental and control group. It is calculated as the mean difference between the experimental and control group divided by the standard deviation of the control group.

Hedges’ correction

Glass’s delta

The following illustration is from the same data shown in the independent t test video. The column with the point estimate contains the value. Notice that all the values are above 1. When you see a value over one, it means that the difference between the two means is larger than one standard deviation. Essentially, the effect size is large, with the most conservative shown here is the Glass’s delta.

Table 111: SPSS Independent Sample Effect Sizes

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