Statistical power

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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 | edit source]

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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 power[edit | edit source]

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

Increasing power[edit | edit source]

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 power[edit | edit source]

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 calculators[edit | edit source]

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

References[edit | edit source]

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

See also[edit | edit source]

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