What is the Difference Between Null and Alternative Hypothesis?

The null and alternative hypotheses are used in statistical hypothesis testing and represent two competing claims about a population. They are mutually exclusive and exhaustive, meaning that one of them must be true, and together they cover every possible outcome.

• Null Hypothesis (H0): This hypothesis predicts no effect or no relationship between variables. It is often abbreviated as H0 and includes an equality symbol (usually =, but sometimes ≥ or ≤). The null hypothesis is the opposite of your research hypothesis and is sometimes described as the "no difference" hypothesis. If there is enough evidence against the null hypothesis, it is rejected in favor of the alternative hypothesis.
• Alternative Hypothesis (Ha or H1): This hypothesis states your research prediction of an effect or relationship between variables. It is the complement to the null hypothesis and often represents the research hypothesis you expect or hope will be true. The alternative hypothesis is the statement that there is a change, difference, or relationship. If the null hypothesis is rejected, it provides evidence for the alternative hypothesis.

For example, if you suspect that girls take longer to get ready for school than boys:

• Null Hypothesis: Girls' time does not exceed boys' time (H0: Girls' time ≤ Boys' time)
• Alternative Hypothesis: Girls take longer to get ready for school than boys (Ha: Girls' time > Boys' time)

In summary, the null hypothesis predicts no effect or no relationship, while the alternative hypothesis states your research prediction of an effect or relationship. When testing these hypotheses, if there is enough evidence against the null hypothesis, it is rejected in favor of the alternative hypothesis.

Comparative Table: Null vs Alternative Hypothesis

Here is a table summarizing the differences between null and alternative hypotheses:

Both null and alternative hypotheses are used in statistical hypothesis testing. The null hypothesis predicts no effect or no relationship between variables, while the alternative hypothesis states your research prediction of an effect or relationship. Researchers and scientists generally try to reject or disprove the null hypothesis, and if there is convincing evidence, they support the alternative hypothesis.