An experimenter is examining the relationship between age and self-disclosure. A large sample of participants that are 25 to 35 years old and participants that are 65 to 75 years old are compared, and significant differences are found with younger participants disclosing much more than older people. The researcher reports an effect size of. 34. What does this mean

It means that in future studies we can expect that 63.00% of young participants will exceed the average value of older individuals, relative to an evaluation of the relationship between age and self-disclosure.

Explanation:

When a research proposes a new approach to a given question, it is often important to consider how much this new approach is better than the ones that are commonly used. This "improvement" is measured by a scale called effect size. The use of effect size adds information to the concept of statistical significance. Increasingly this type of approach has been stimulated, in some cases even required, by scientific publications.

The effect size calculation is therefore an important complement to the null hypothesis test of significance, since it is allowed to measure a potential real significance of an effect in an intervention by describing the size of the effects observed, which is independent of a possible misleading effect as a function of sample size.