The magnitude of the difference or relationship you expect to find, often estimated from previous studies or pilot data. Population Variance (
Can lead to "Type I errors" (false positives) or find "statistically significant" results that have zero practical or clinical importance. 2. The Four Pillars of Calculation sampling size calculation
This is the probability that your confidence interval actually contains the true population parameter. Standard values are 90%, 95%, and 99%. A 95% confidence level means that if you took 100 random samples, 95 of them would produce an interval containing the true population value. A higher confidence level (e.g., 99%) requires a larger sample size. The magnitude of the difference or relationship you
Usually set at 0.05, representing a 5% risk of concluding a difference exists when it does not (Type I error). Statistical Power ( The Four Pillars of Calculation This is the
This is perhaps the most subjective part. It’s the "magnitude" of the difference you expect to see.Smaller expected effects require much larger sample sizes to detect. D. Population Standard Deviation (Variance)