Hypothesis testing is a statistical method used to determine whether a hypothesis about a population parameter is supported by the sample data. It involves the following steps:

1. State the null hypothesis (H0) and the alternative hypothesis (Ha).
2. Determine the appropriate test statistic and the level of significance (alpha).
3. Collect the sample data and calculate the test statistic.
4. Determine the p-value, which is the probability of obtaining a test statistic as extreme as the observed one, assuming the null hypothesis is true.
5. Compare the p-value to the level of significance. If the p-value is less than or equal to alpha, reject the null hypothesis; otherwise, fail to reject the null hypothesis.
6. Interpret the results in the context of the problem.

Hypothesis testing is used in a variety of fields, including business, medicine, psychology, and engineering, to make decisions based on data and to test theories and hypotheses.