# Statistical power

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- return a significant result based on a sample from a population in which there is a real effect.
- 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 H_{0} (i.e., getting a significant result when there is a real difference in the population).

## Desirable power[edit]

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

## Increasing power[edit]

Power will be higher when the:

- effect size (ES) is larger
- sample size (N) is larger
- critical value (α) is larger

## Estimating power[edit]

Statistical power can be calculated prospectively and retrospectively.

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

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

Report actual power in the results.

## Power calculators[edit]

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:

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

## References[edit]

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

## See also[edit]

Search for on Wikipedia.
Statistical power |