Hypothesis testing refers to the process of making inferences or educated guesses about a particular population parameter. This can either be done using statistics and sample data, or it can be done on the basis of an uncontrolled observational study. When a pre-determined number of subjects in a hypothesis test prove the "alternative hypothesis," then the original hypothesis (the "null hypothesis") is overturned.
Below, you will find some examples of hypothesis testing in a variety of different cases.
Hypothesis testing is very important in the scientific community and is necessary for advancing theories and ideas. Statistical hypothesis tests are not just designed to select the more likely of two hypotheses—a test will remain with the null hypothesis until there's enough evidence to support the alternative hypothesis. Now you have seen several examples of hypothesis testing and you can better understand why it is so important. For more information on types of hypotheses see Examples of Hypothesis.