Rejection of a true null hypothesis is?

Appeared in: RUHS, Jaipur, M.Sc Nursing Entrance Exam-2016

Explanation

A Type I error occurs when a researcher incorrectly rejects a null hypothesis that is, in fact, true.
This type of error is also known as an alpha (α) error or a 'false positive'.
It means concluding that there is a statistically significant effect or relationship when one does not actually exist in the population.
The probability of making a Type I error is determined by the significance level (alpha) set by the researcher, typically 0.05 (5%) or 0.01 (1%).

Option B: A Type II error is the opposite of a Type I error. It involves failing to reject a null hypothesis that is actually false.
Option C: Sampling error refers to the natural variation and inaccuracies that arise when a sample is used to estimate a population parameter. It's not an error in the decision-making process of hypothesis testing.
Option D: This option is incorrect because the rejection of a true null hypothesis has a specific name in statistics, which is Type I error.

Clinical Relevance

Nursing practice connection: This is primarily an exam-oriented knowledge point with limited direct bedside application, so retain Types of errors in hypothesis testing as background academic context rather than a clinical decision trigger.
Understanding Type I and Type II errors is critical for evidence-based nursing practice, as it allows nurses to critically appraise research findings.
A Type I error in a clinical trial could lead to the adoption of a new, ineffective, or even harmful treatment, believing it works when it doesn't.
A Type II error could cause a potentially beneficial treatment to be discarded because the study failed to detect its effect, thus hindering medical progress.

How to Approach the Question

First, identify the key terms in the question: 'rejection' and 'true null hypothesis'.
This is a factual recall question from biostatistics, requiring knowledge of the definitions of errors in hypothesis testing.
Recall the definition of a Type I error: It is the error of rejecting a null hypothesis when it is actually true (a 'false positive').
Recall the definition of a Type II error: It is the error of failing to reject a null hypothesis when it is actually false (a 'false negative').
Compare the question's statement with these definitions. 'Rejection of a true null hypothesis' directly matches the definition of a Type I error.
Eliminate other options. Sampling error is a different concept related to sample-population discrepancy, not decision-making.

Concept Tested & Keywords

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E6 NursingResearch Polit 11e Part 1 pp. 404-406, 403-405

E6 NursingResearch Suresh Sharma 5e Part 2 p. 188-190

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