In statistical hypothesis testing, a Type II error occurs when a researcher fails to reject a false null hypothesis. This means that the researcher concludes that there is no statistically significant difference between two groups when, in reality, there is a difference.
There are a number of ways to avoid making a Type II error, including increasing the sample size, using a more powerful statistical test, and reducing the variability in the data.