What you’ll learn to do: Describe Type I and Type II errors and explain their consequences

If the null hypothesis is true, the sample should lead us to that conclusion. If the null hypothesis is false, the sample should lead us to that conclusion, too. However, sometimes the data might not lead to the correct conclusion. For example, we happen to randomly choose many people who are above the true mean height in a sample of 50 adults and this leads us to conclude that the mean height of U.S. adults is now higher than it was twenty years ago. If the mean height has not in fact changed, this would be considered an error.