Practical significance can be derived from which of the following measures?

The concept of practical significance relates to the importance of the effect or difference in a real-world context, beyond just statistical significance. Effect size is a quantitative measure that indicates the magnitude of a phenomenon. It provides a clear indication of the strength of the relationship or the size of the difference being examined in research findings.

By evaluating effect size, researchers can determine whether the observed effects are not only statistically significant but also meaningful in practical terms. For instance, a small effect size might indicate a statistically significant result that has little relevance or importance in real-world applications, while a large effect size suggests that the finding has considerable implications.

Other measures, while valuable in their own right, do not convey practical significance as directly as effect size does. Confidence intervals offer insight into the reliability of the estimate but do not quantify the size of an effect. P-values indicate whether results are statistically significant but do not measure how large or consequential an effect is. Standard errors provide an estimate of the variability of a sample statistic but do not address the importance or relevance of the findings in practice. Thus, effect size is the key measure for determining practical significance.