Statistical power is a function of several factors:
Sample Size: Larger sample sizes generally increase power. Effect Size: The magnitude of the difference or relationship being studied. Larger effect sizes make it easier to detect differences. Significance Level (α): The probability of making a Type I error (false positive). Commonly set at 0.05. Variability: Lower variability within the data increases power.
Power analysis can be conducted using statistical software to determine the necessary sample size before starting an experiment.
