You can use any of the following methods to increase the power of a hypothesis test.

- Use a larger sample
- Using a larger sample provides more information about the population and, thus, more power. Using a larger sample is often the most practical way to increase power.
- Use a higher significance level (also called alpha or α)
- Using a higher significance level increases the probability that you reject the null hypothesis. However, be cautious, because you do not want to reject a null hypothesis that is actually true. Rejecting a null hypothesis that is true is called type I error.
- Choose a larger value for the difference
- It is easier to detect larger differences in population means or proportions.
- Use a one-sided hypothesis
- A directional hypothesis has more power to detect the difference that you specify in the direction that you specify. (The direction is either less than or greater than.) However, be cautious, because a directional hypothesis cannot detect a difference that is in the opposite direction.
- Improve your process
- For a hypothesis test of means (1-sample Z, 1-sample t, 2-sample t, and paired t), improving your process decreases the standard deviation. When the standard deviation is smaller, the power increases and smaller differences can be detected.