In: Psychology
After conducting an experiment, you report a p-value of less than .05 and an effect size of .82. Explain what this means.
The p-value shows, if the results are significant or not. Whereas, the effect size shows the extent to which they are significant or how much effect they have. A data with p-value lower than or equal to the level of significance (0.05, here) is considered to be significant. According to Cohen's criteria, if the effect size value (d) is 0.2 or close to it, then the effect size is small, if the value is 0.5, then the effect size is medium, if the value is 0.8, then the effect size is large.
Hence, in the question it is stated that the p-value is less
than .05 which indicates that the results are statistically
significant at 0.05 level of significance, with a large effect size
of .82
This means that if we were trying to find the impact of a medicine
on anxiety (for example) in the experiment, then the results have
shown to have an impact of the medicine on anxiety, i.e., the
results were statistically significant. Now, we know that the
medicine is effective but how much? This is shown by the effect
size of .82, which indicates the magnitude at which the medicine
was effective, i.e., the medicine had large effect or impact on
anxiety.