The probability that an experiment will find an effect if that effect exists in the total population. The number of observations in the study sample greatly influences statistical power.
Having enough data to reach the desired goal in a statistical study.
This is a phrase used to indicate how likely a study is to give an accurate answer, according to the number of patients that will be included in the trial.
A mathematical quantity that indicates the probability a study has of obtaining a statistically significant effect. A high power of 80 percent, or 0.8, indicates that the study - if conducted repeatedly - would produce a statistically significant effect 80 percent of the time. On the other hand, a power of only 0.1 means there would be a 90 percent chance that the research missed the effect - if one exists at all.
The power of a statistical test is the probability that the test will reject a false null hypothesis, or in other words that it will not make a Type II error. As power increases, the chances of a Type II error decrease, and vice versa. The probability of a Type II error is referred to as Î².