Vaikutuskokoarvot

Vaikutuskokoarvot, often translated as effect size, are quantitative measures of the magnitude of a phenomenon. In statistical analysis, they represent the strength of the relationship between two variables or the difference between two groups, independent of sample size. Unlike p-values, which indicate the probability of observing the data if the null hypothesis were true, effect sizes convey the practical significance or importance of the finding.

Commonly used effect size measures include Cohen's d for comparing means, Pearson's r for correlations, and eta-squared for analysis of variance. Cohen's d, for example, standardizes the difference between two means by the standard deviation, providing a dimensionless value that can be interpreted across different studies. A small effect size might be around 0.2, a medium around 0.5, and a large around 0.8.

Understanding effect sizes is crucial for interpreting research findings. A statistically significant result with a small sample size might have a trivial practical impact, whereas a study with a larger sample might detect even small effects with high statistical power. Effect sizes help researchers and readers assess the real-world implications of their results and make informed decisions about the importance of observed differences or relationships. They are also essential for meta-analyses, which combine results from multiple studies to estimate an overall effect size.