Statistical power detect true effect – UGC NET Question

Statistical power quantifies the sensitivity of a test to identify real effects when they exist. It is mathematically equal to one minus beta, where beta is the probability of a Type II error. High power means that the test is unlikely to miss true differences or relationships. Therefore, the probability described in the stem is called the power of the test.

Option A:
Precision refers to how close repeated estimates are to one another, such as narrow confidence intervals, but it is not the standard term for the probability of detecting true effects.

Option B:
Power is influenced by factors such as sample size, effect size, significance level and variability in the data. Researchers often conduct power analyses while designing studies to ensure that they have a reasonable chance of finding meaningful effects. This focus on correctly rejecting false null hypotheses matches the stem, making this option correct.

Option C:
Reliability concerns the consistency of measurements over time or across items and is a property of instruments, not directly of hypothesis tests.

Option D:
Validity relates to the appropriateness of inferences drawn from test scores or study designs; it does not specifically denote the probability of detecting true effects in statistical testing.