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NISM Certifications · NISM-Series-XV: Research Analyst · Fundamentals of Research

A research analyst tests whether a stock's returns differ from the market's. Rejecting a null hypothesis that is actually true is known as which error?

Rejecting a null hypothesis that is actually true is called a Type I error, a false positive. It is controlled by the significance level. A Type II error is the opposite mistake, failing to reject a null hypothesis that is actually false.

  1. AType II error
  2. BSampling error
  3. CType I errorCorrect
  4. DMeasurement error

Explanation

A Type I error is rejecting a true null hypothesis (a false positive). A Type II error is failing to reject a false null hypothesis. Sampling and measurement errors are different concepts unrelated to hypothesis decisions.

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