Which of the following best describes a null hypothesis?

• A. A statement of no effect or no difference.
• B. A statement predicting a direction of effect.
• C. A statement about data collection methods.
• D. A statement about statistical significance only.

Answer: (A)

The main idea here is how a null hypothesis functions in hypothesis testing. The null hypothesis is the default assumption that there is no effect or no difference in the population. It posits that a population parameter equals a specific value (for example, no difference between groups). The purpose of the test is to see whether the observed data provide enough evidence to conclude that this claim is unlikely. If the data are unlikely under the null, we reject it and infer there is an effect or difference; if not, we fail to reject the null.

The other descriptions don’t fit as well. A direction of effect describes the alternative hypothesis, not the null. Data collection methods relate to study design, not the hypothesis about the population parameter. Significance refers to the outcome of the test (how unlikely the data are if the null is true) rather than defining what the null states.