How does the sample size relate to the power of a test?
- It depends on the effect size
- Larger sample sizes decrease power
- Larger sample sizes increase power
- Sample size has no influence on power
Larger sample sizes increase the power of a test because they provide more data, reducing the influence of random error and making it easier to detect an effect if one exists. This is why researchers often aim to recruit as large a sample as possible, within the constraints of their resources.
Loading...
Related Quiz
- What can the Mann-Whitney U test tell you about the shape of your distributions?
- A negative value of skewness indicates that the distribution is skewed to the ________.
- The Pearson's Correlation Coefficient measures the ________ between two variables.
- In what situations can the use of stepwise regression for model selection be problematic?
- How does the effect size relate to the power of a t-test?