Beta risk, also known as type II error, occurs when a statistical test fails to reject a false null hypothesis, leading to the incorrect conclusion that there is no effect or difference when one actually exists. This risk is inversely related to the power of the test, which is the probability of correctly rejecting a false null hypothesis.

Beta Risk

A Type II error occurs when a statistical test fails to reject a false null hypothesis, leading to a false negative result. It is inversely related to the power of a test, meaning that as the probability of a Type II error decreases, the test's ability to detect an effect when there is one increases.

Type II Error

A statistical test is a method used to determine if there is a significant effect or relationship present in a dataset, often by comparing observed data against a null hypothesis. The choice of test depends on the data type, distribution, and the specific research question being addressed.

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