NULL HYPOTHESIS
In statistics, a null hypothesis is a statement or assumption that there is no significant
difference between two or more groups, variables, or populations. The null hypothesis is
typically denoted as "H0" and is often used in hypothesis testing.
The null hypothesis matters because it provides a benchmark for comparing the results of a
statistical analysis. When conducting hypothesis testing, researchers compare the observed
data to what would be expected under the null hypothesis. If the observed data are unlikely
to have occurred by chance under the null hypothesis, then the null hypothesis is rejected in
favor of an alternative hypothesis.
For example, suppose a researcher wants to test the hypothesis that a new drug is more
effective at treating a disease than a placebo. The null hypothesis would be that there is no
significant difference between the two treatments, while the alternative hypothesis would be
that the new drug is more effective. The researcher would then collect data on the outcomes
of patients who received the drug and the placebo and compare the observed differences to
what would be expected under the null hypothesis. If the observed differences are unlikely to
have occurred by chance, the null hypothesis would be rejected in favor of the alternative
hypothesis, indicating that the new drug is more effective.
The null hypothesis is an essential component of statistical analysis because it allows
researchers to draw conclusions based on empirical evidence rather than intuition or
personal biases. By testing hypotheses against a null hypothesis, researchers can determine
whether the observed differences between groups or variables are statistically significant,
which helps to ensure the validity and reliability of their findings.