Hypothesis Testing

Hypothesis testing is a statistical method used to assess whether a claim (hypothesis) about a population is likely true based on evidence from a sample.

It involves formulating two opposing hypotheses: the null hypothesis (H0), which represents the default assumption of no difference or effect, and the alternative hypothesis (Ha), which proposes the opposite. We collect data from a sample of the population and use statistical calculations to determine the probability of observing such data if the null hypothesis were true. This probability is called the p-value. If the p-value is very low (typically below 0.05), we reject the null hypothesis and tentatively support the alternative hypothesis.

It’s important to remember that hypothesis testing doesn’t definitively prove anything, but rather provides strong evidence for or against a claim based on the sample data.