Statistical Methods for Hypothesis Testing
Statistical Methods for Hypothesis Testing Hypothesis testing helps us decide whether observed data reflect a real effect or random variation. The idea is simple: we start with a null hypothesis that nothing changes, and an alternative that something meaningful does. The goal is not to prove the null, but to assess how compatible the data are with it. A clear plan makes the results easier to trust. Plan first: choose a significance level, often 0.05. Then collect data and compute a test statistic that summarizes the evidence against the null. The p-value measures how extreme the observed result would be if the null were true. A small p-value means the data look unlikely under the null. ...