His measure for effect size is called Cohen’s d. To provide more insight into the size of an effect, Cohen (1988) proposed the so-called effect size. Thus, a significant effect is not equal to a large effect. Something is significant or not, but it does not imply anything about the size of the effect. Another point of critique is that a significant effect does not imply anything about the effect size. We do not know whether the null hypothesis is truly false or true. Based on the sample data, the null hypothesis is rejected or not. When the null hypotheses is rejected, we make statements about the sample data and not about the null hypothesis. When testing hypotheses, most attention is paid to the data instead of to the hypotheses. The main critique refers to the interpretation of a significant result.
Some researchers critize the process of testing hypothesis.
