State two reasons why including the p-value is prudent when you are reporting the results of a hypothesis test.

In general as we know when we perform a hypothesis test in statistics then p value help us to determine the significance of our result.
Hypothesis test are generally used to test a validity of claim that is made about a population.This claim that's on trial in essence is called as a Null Hypothesis.

The p - values is a number between 0 to 1 and interpreted in following way:

A small p - value (<= 0.05) indicates the strong evidence against a null hypothesis , so you reject a null hypothesis.

A large p - value (>0.05) indicates weak evidence against a null hypothesis , so you fail to reject the null hypothesis.

The reason which include the p - value is prudent when you are reporting the result of a hypothesis test are given below:

1. It allows us for evaluating the strength of the evidence against the null hypothesis.

2. Allow us for assessing significance at any desired level . The null hypothesis can be rejected at any significance level larger than or equal to p -  value and it can not be rejected at any significance level smaller than the p - value.

Sis less than or equal to 75 (bottom left)