UGC NET Questions (Paper – 1)

A Type I error occurs when a researcher concludes that an effect or difference exists in the population when in fact the null hypothesis is true. It is analogous to a false positive decision. The probability of committing a Type I error is controlled by the significance level alpha, such as 0.05. Therefore, the error of rejecting a true null hypothesis described in the stem is called a Type I error.

Option A:
Type II errors occur in the opposite situation, when a false null hypothesis is not rejected, corresponding to a false negative; this is not the scenario given.

Option B:
Random error refers broadly to unpredictable fluctuations in data due to chance influences, not specifically to the decision error of rejecting a true null hypothesis.

Option C:
Systematic error involves consistent bias in measurement or procedure, which affects estimates but does not directly define the statistical decision about hypotheses.

Option D:
Type I errors are a central concern in hypothesis testing because setting a low alpha reduces their likelihood, though it may increase Type II errors. This link with rejecting true null hypotheses fits the stem exactly, making this option correct.