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2003•BestuursdinamikaRequires access

Practical significance (effect sizes) versus or in combination with statistical significance (p-values) : research note

Samuel Ellis, H.S. Steyn

Open publisher page 253 citations

Abstract

Statistical significance tests have a tendency to yield small p-values (indicating significance) as the size of the data sets increase. The effect size is independent of sample size and is a measure of practical significance. It can be understood as a large enough effect to be important in practice and is described for differences in means as well as for the relationship in two-way frequency tables and also for a multiple regression fit.

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What this paper is about

Statistical significance tests have a tendency to yield small p-values (indicating significance) as the size of the data sets increase. The effect size is independent of sample size and is a measure of practical significance. It can be understood as a large enough effect to be important in practice and is described for differences in means as well as for the relationship in two-way frequency tables and also for a multiple regression fit.

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OpenAlex reports 253 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

Statistical significance tests have a tendency to yield small p-values (indicating significance) as the size of the data sets increase. The effect size is independent of sample size and is a measure of practical significance. It can be understood as a large enough effect to be important in practice and is described for differences in means as well as for the relationship in two-way frequency tables and also for a multiple regression fit.

Key concepts: Statistical significance, Statistics, Sample size determination, Significance testing, Mathematics, Statistical hypothesis testing, Econometrics, Regression analysis

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