Statistical power and limited variance of effect size
Limited variance of outcome will increase statistical power and decrease the needed sample size
Limited variance in the outcome means that significant effects will be easier to detect. More observations will fall closer to the mean and confidence intervals will be constricted, leading to more confidence and precision in treatment effects. Limited variance or homogeneity in a distribution will lead to more precise values and dispersal of observations.
When conducting research, it is often wise to overestimate the amount of variance in an outcome. It is good practice because it forces researchers to collect more observations of an outcome and decreases the risk of committing Type II errors.
When conducting research, it is often wise to overestimate the amount of variance in an outcome. It is good practice because it forces researchers to collect more observations of an outcome and decreases the risk of committing Type II errors.
Limited variance in the outcome will increase statistical power and decrease the needed sample size.
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