In statistics, what is a null hypothesis?

The null hypothesis is defined as a statement that suggests no effect or relationship exists between the variables being studied. It serves as a default or baseline assumption in statistical hypothesis testing. Essentially, researchers use the null hypothesis to provide a contrast against an alternative hypothesis, which suggests that there is an effect or relationship. By establishing the null hypothesis, statisticians can conduct tests to determine if there is enough evidence to reject it in favor of the alternative hypothesis.

For example, in testing a new medication, the null hypothesis might state that the medication has no effect on patients compared to a placebo. If statistical analysis leads to rejecting the null hypothesis, it would indicate support for the idea that the medication does have an effect.

In the context of the other options, the second choice misrepresents the nature of hypotheses in statistical testing; hypotheses are subject to testing and may be rejected based on evidence. The third choice confuses hypothesis testing with a statistical value; rather, test statistics are derived from the data to help assess the null hypothesis. The fourth choice describes a method rather than a hypothesis itself, as hypothesis testing is about evaluating a claim rather than simply invalidating a theory.