P-value Formula

About P-value Formula

The probability value formula is abbreviated as P-value. The probability of having a result that is either the same as or more extreme than the other real observations is defined by the P-value. The chance of an event occurring is represented by the P-value. The P-value formula is used instead of the rejection point to determine the least significance at which the null hypothesis is rejected. Given observed and expected frequencies, the lower the P-value, the stronger the evidence in favour of the alternative hypothesis. More Maths Formulas on the parent's page.

P-value is a statistical measure that can be used to determine whether or not a hypothesis is valid. The P-value is always between 0 and 1. The level of significance() is a predetermined criterion that the researcher should set. It is usually set to 0.05. P-value is calculated using the following formula:

Steps to calculate P-value Formula

Step 1: Find out whether test static Z is

 $Z = \frac{\hat{p} -p0}{\sqrt{{\displaystyle \frac{p0(1 -p0)}{n}}}}$

Where,

• $\hat{p}$ = Sample Proportion
• P0 = assumed population proportion in the null hypothesis
• N = sample size

Step 2:Look at Z-table to find the corresponding level of P from the z value obtained.

 $Z = \frac{\hat{p} -p0}{\sqrt{{\displaystyle \frac{p0(1 -p0)}{n}}}}$

Where,

• $\hat{p}$ = Sample Proportion
• P0 = assumed population proportion in the null hypothesis
• N = sample size

P-value Formula

The formula to calculate the P-value is:

 $Z = \frac{\hat{p} -p0}{\sqrt{{\displaystyle \frac{p0(1 -p0)}{n}}}}$

Where,

• $\hat{p}$ = Sample Proportion
• P0 =assumed population proportion in the null hypothesis

P-value Table

The P-value table helps in determining the hypothesis according to the p-value.