Null hypothesis

• A. A general statement that there is no relationship between two measured phenomena
• B. The alternative hypothesis that there is a relationship
• C. Data will definitely show a difference
• D. The sample size determines the significance

Answer: (A)

The null hypothesis is a statement that there is no relationship or effect between the variables being studied. It gives you a baseline to test against and is the default position researchers try to disprove with the data. That’s why the choice describing no relationship between two measured phenomena fits best—it captures the standard idea of H0: no association, no difference.

The other ideas don’t fit as well. The alternative hypothesis expresses that there is a relationship or difference, which is the competing claim to be supported if the null is rejected. Saying data will definitely show a difference isn’t accurate because statistical testing deals with probabilities and sampling variability, so results may be significant or not. Finally, while larger sample sizes can increase the ability to detect a true effect, significance is determined by the observed data relative to variability and the chosen alpha level, not simply by the sample size itself.