Sample sizes of at least 85 are needed to get reliable averages and variations in test data, no matter how skewed the data is. Researchers in Brisbane, Australia looked at 12 different measures from 7 tests to figure this out. They found that smaller sample sizes work okay for skewed data, but for more accurate results, you need a bigger sample size.