Type II error is a failure of rejection of a false null hypothesis (or a null hypothesis that is not true and should be rejected). However, in some cases, researchers erroneously make a decision that it should not be rejected. Simply, this error is false negative. This entry provides a description of Type II error and a relationship between Type I and Type II errors.
When researchers make decisions on statistical testing results based on a p value, there is a chance that researchers might make errors such as Type II error by accepting a false null hypothesis. That is, the truth in a population is that a research hypothesis (alternative hypothesis), which predicts that there ...
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