A Type II error in a clinical trial means:

• A Concluding a treatment works when it does not (false positive)
• B Selecting a biased sample from the population
• C Using the wrong statistical test for the data distribution
• D Failing to detect a true treatment effect (false negative) ✓

Explanation

Type II error (β error) is a false-negative error: failing to reject the null hypothesis when it is actually false—i.e., concluding the treatment has no effect when it truly does. The power of a study (1−β) quantifies the probability of correctly detecting a true effect. Type I error (α) is the false positive. Type II error is reduced by increasing sample size, effect size, or reducing measurement variability.

Reference: Park's Textbook of Preventive and Social Medicine, 27th ed.

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Written and medically reviewed by the StethoPrep medical team.