Hypothesis testing involves formulating a null hypothesis (H0) and an alternative hypothesis (H1), collecting data, and analyzing it using statistical tests (e.g., t-tests or chi-square tests). The p-value is used to determine whether the null hypothesis should be rejected or not, based on the significance level (usually 0.05). If the p-value is below 0.05, the null hypothesis is rejected, indicating a statistically significant result.