I error increases, the probability of committing a Type II error decreases. Ultimately, we want to reject the null hypothesis when it should be rejected. Refer to the following matrix for a graphical representation of this relationship. It is also the level of significance that is established by the researcher.
Power increases as sample size increases.
When sample size is increased, the standard error of the mean is decreased. Power increases as the variability in the population decreases. By decreasing the probability of committing a Type II error, we also increase power. We can make a personal assessment of what constitutes an important difference between m hyp , and m real .