an act in statistics whereby an analyst tests an assumption regarding a population parameter.

This process is known as Hypothesis Testing. Here are the steps involved:

1. Formulate the Null Hypothesis (H0): The null hypothesis is a statement about the population that either is believed to be true or is used to put forth an argument unless it can be shown to be incorrect beyond a reasonable doubt.

2. Formulate the Alternative Hypothesis (H1): The alternative hypothesis is a statement that directly contradicts the null hypothesis by stating that that the actual value of a population parameter is less than, greater than, or not equal to the value stated in the null hypothesis.

3. Choose the Significance Level (α): The significance level is a probability threshold that determines when you reject the null hypothesis.

4. Determine the Test Statistic: This is a quantity derived from the sample and used in the test procedure. The form of the test statistic depends on the type of null hypothesis, the type of sampling, and the available data.

5. Calculate the P-value: The P-value is the probability that a test statistic at least as significant as the one observed would be obtained assuming that the null hypothesis were true. The smaller the P-value, the stronger the evidence against the null hypothesis.

6. Make a Decision: If the P-value is less than the chosen significance level, you reject the null hypothesis. Otherwise, you fail to reject the null hypothesis