Statistical power

Completion status: this resource is ~50% complete.
Educational level: this is a tertiary (university) resource.

Statistical power is the likelihood that a statistical test will:

  1. return a significant result based on a sample from a population in which there is a real effect.
  2. reject the null hypothesis when the alternative hypothesis is true (i.e. that it will not make a Type II error).

Power can range between 0 and 1, with higher values indicating a greater likelihood of detecting an effect.

What is statistical power?Edit

 

Statistical power is the probability of correctly rejecting a false H0 (i.e., getting a significant result when there is a real difference in the population).

Desirable powerEdit

  1. Power ≥ .80 generally considered desirable
  2. Power ≥ .60 is typical of studies published in major psychology journals

Increasing powerEdit

Power will be higher when the:

  1. effect size (ES) is larger
  2. sample size (N) is larger
  3. critical value (α) is larger

Estimating powerEdit

Statistical power can be calculated prospectively and retrospectively.

If possible, calculate expected power before conducting a study, based on:

  1. Estimated N,
  2. Critical α,
  3. Expected or minimum ES (e.g., from related research)

Report actual power in the results.

Power calculatorsEdit

Try searching using terms such as "statistical power calculator" and maybe also the type of test, and you should turn up links to useful pages such as:

  1. Statistical power calculators
  2. One Sample Test Using Average Values
  3. Post-hoc Statistical Power Calculator for Multiple Regression

ReferencesEdit

  1. Cohen, J. (1992). Power primer. Psychological Bulletin, 112, 155-159.

See alsoEdit

  Search for Statistical power on Wikipedia.