UGC NET Questions (Paper – 1)

The null hypothesis serves as a default position stating that any observed difference or association in the sample is due to chance. It posits no real effect, no difference or no relationship at the population level. Statistical tests assess whether the sample data provide enough evidence to reject this assumption. Thus, H0 represents the benchmark against which alternative claims are evaluated.

Option A:
Option A correctly captures the idea that the null expresses absence of effect or relationship. It is framed in a way that can be tested using probability models and sampling distributions. If evidence contradicts H0 beyond a chosen significance level, it may be rejected.

Option B:
Option B suggests that the null is what the researcher wants to prove at any cost, which is incorrect. Researchers often hope to reject the null in favor of their alternative hypothesis, but they must do so based on evidence, not desire.

Option C:
Option C claims that the null cannot be tested, which contradicts its very role in inferential statistics. Hypothesis tests are structured specifically around assessing H0.

Option D:
Option D concerning sample size is unrelated to the content of the null hypothesis. Sample size affects power but is not itself expressed in H0.