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A Type II error is a false negative in null hypothesis testing. It occurs when a researcher mistakenly concludes that their results are not statistically significant—thereby retaining the null hypothesis—when, in reality, the null hypothesis is false and a true relationship does exist in the population. In practical research, Type II errors typically happen because a study lacks adequate statistical power to detect the underlying relationship, often due to an insufficiently large sample size.

Type II Error

In psychological research, replication involves repeating another scientist's experiment, often using new samples, to assess the reliability of the original findings. Because any single study carries a risk of reflecting a Type I or Type II error, researchers must be cautious when interpreting isolated results. Each successful replication of a study that produces a similar outcome provides increasing confidence that the finding represents a genuine, real-world phenomenon rather than a statistical artifact.

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