According to Matsumoto and his colleagues, the general class of statistical procedures that helps to determine the degree to which differences in mean values reflect meaningful differences among individuals is called:

The answer is the effect size statistics.

Explanation:

Effect sizes are considered a way through which it could be a description of different important relations established among population parameters. This is a type of quantitative representation related to the importance of relations or comparisons that are considered meaningful concerning the research design in which they have been applied.

Some examples of effect sizes are the correlation between two variables, the mean difference, or the risk of a particular event. Effect sizes have a relevant role in aspects like power analyses, sample size planning, as well as in meta-analyses.      

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