Statistical tests for effects are based on a ratio of the size of the difference in the sample means and sampling error to allow us to determine what part of the mean difference is due to the effect and which part is due to sampling error.

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This statement is true. Statistical tests, such as t-tests and ANOVA, assess whether the difference in sample means is statistically significant, which means that the likelihood of the difference being due to chance (sampling error) is low. By comparing the size of the mean difference to the standard error of the mean, researchers can estimate the effect size and determine how much of the observed difference is due to the intervention or experimental manipulation being tested.

Statistical Tests for Effects Are Based on a Ratio of the Size