Reporting results from independent samples t-test in SPSS

// Reporting results from independent samples t-test in SPSS //

The indepeendent (two) samples t-test in SPSS usually consists of two parts:
First, the independent samples t-test itself, which compares the means of the two groups with eachother. Field (2018), p. 259 advises to use the corrected values, since no violation of heterogeneity of variances automatically leads to no correction.

Second, in the case of a significant difference - the effect size Cohen's d, or Hedges correction of Cohen's d (see Grissom, Kim (2012), p. 62-71).

The reporting is limited to the essentials: t-value including degrees of freedom, p-value and effect size. The latter is also to be classified, optionally with Cohen (1992): A Power Primer, or the respective research field-specific limits.


Sample formulation:
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The trained Group was able to do more reptitions of Exercise XYZ (M = 61.00, SD = 8.84) than the untrained group (M = 52.6, SD = 9.16), t (28.7) = 2.6, p = .007, d = 0.91.
The difference is large, according to Cohen (1992)."


📚 Literature
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📚 Field, A. (2018). Discovering statistics using IBM SPSS statistics. sage.

📚 Grissom, R. J., & Kim, J. J. (2012). Effect sizes for research: Univariate and multivariate applications. Routledge.


⏰ Timestamps:
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0:00 Introduction and overview
0:08 Correction or no correction?
0:21 Two sample t-test results
0:45 Effect size Cohen's d and Hedges' correction


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