What is Hypothesis testing?

Data Science, AI and ML
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#1

Hypothesis testing.

#2

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.
#3

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.