What is a null hypothesis?

• A. A statement of no effect or no difference that is tested statistically.
• B. The range of data collected in a sample.
• C. A method for improving experimental throughput.
• D. An alternative to the null hypothesis.

Answer: (A)

A null hypothesis is a default assumption in statistics that there is no effect or no difference between groups. When you run an experiment, you use data to test whether any observed difference could plausibly happen by chance if nothing is really changing. For example, if you’re checking whether a new method changes how often a mammal is detected, the null would say detection is the same with or without the method. We compute a p-value to see how likely the observed data would be if this no-difference assumption were true. If the p-value is small enough, you reject the null and say there’s evidence of an effect; if not, you don’t have enough evidence to claim a real difference. The other options don’t fit because they describe data Range, study design, or an alternative statement that’s tested against the null, not the null itself.