Hypothesis testing.
Hypothesis testing is an act in statistics whereby an analyst tests an assumption regarding a population parameter. The methodology employed by the analyst depends on the nature of the data used and the reason for the analysis.
The hypothesis is tested using a four-step process:
- The first step is for the analyst to state the two hypotheses so that only one can be right.
- The next step is to formulate an analysis plan, which outlines how the data will be evaluated.
- The third step is to carry out the plan and physically analyze the sample data.
- The fourth and final step is to analyze the results and either reject the null hypothesis, or state that the null hypothesis is plausible, given the data.
Usually in Hypothesis testing, we evaluate two mutually exclusive statements about a population to determine which statement is best supported by the sample data.
Based on that, a hypothesis testing can be done for virtually any field of science or even life.
We might have heard from our friends that a particular shop makes very good pizza or burger. With that information, we might order in or go there and eat the said burger/pizza. This act is basically a hypothesis testing. We test if the pizza is actually good by going to the restaurant based on limited info our friends gave.