A null hypothesis (denoted as Hâ‚€) is a fundamental concept in statistical hypothesis testing that asserts there is no effect, no difference, or no relationship between the variables or groups being studied. It essentially proposes that any observed differences or patterns in data are due to random chance rather than a true underlying effect
. In research, the null hypothesis serves as the default or starting assumption. For example, if comparing test scores between two groups, the null hypothesis might state that the mean scores of both groups are equal (no difference)
. Researchers then use statistical tests to determine whether there is enough evidence to reject the null hypothesis in favor of an alternative hypothesis, which claims that a real effect or difference does exist
. Key points about the null hypothesis:
- It claims "no effect" or "no difference" in the population.
- It is tested against sample data to assess if observed effects are statistically significant.
- Failing to reject the null hypothesis means there is insufficient evidence to support a real effect, but it does not prove the null hypothesis true.
- Rejecting the null hypothesis suggests the alternative hypothesis may be true, indicating a statistically significant effect
Thus, the null hypothesis is central to scientific research and statistical inference, providing a baseline to test whether observed data reflect genuine phenomena or random variation
