Pvalue Formula
The Pvalue formula is short for probability value. Pvalue defines the probability of getting a result that is either the same or more extreme than the other actual observations. The Pvalue represents the probability of occurrence of the given event. The Pvalue formula is used as an alternative to the rejection point to provide the least significance for which the null hypothesis would be rejected. The smaller the Pvalue, the stronger is the evidence in favor of the alternative hypothesis given observed frequency and expected frequency.
What is Pvalue Formula?
Pvalue is an important statistical measure, that helps to determine whether the hypothesis is correct or not. Pvalue always only lies between 0 and 1. The level of significance(α) is a predefined threshold that should be set by the researcher. It is generally fixed as 0.05. The formula for the calculation for Pvalue is:
Step 1: Find out the test static Z is
\(Z = \frac{\hat{p}p 0}{\sqrt{\frac{p 0(1p 0)}{n}}}\)
Where,
 \(\hat{p}=\)Sample Proportion
 \(\mathrm{P0}=\) assumed population proportion in the null hypothesis
 N = sample size
Step 2: Look at the Ztable to find the corresponding level of P from the z value obtained.
Pvalue Formula
The formula to calculate the Pvalue is:
\(Z = \frac{\hat{p}p 0}{\sqrt{\frac{p 0(1p 0)}{n}}}\)
Where,
\(\hat{p}=\)Sample Proportion
\(\mathrm{P0}=\) assumed population proportion in the null hypothesis
Pvalue Table
The belowmentioned Pvalue table helps in determining the hypothesis according to the pvalue.
Pvalue  Description  Hypothesis Interpretation  
Pvalue ≤ 0.05 

Rejected  
Pvalue > 0.05 

Accepted or it “fails to reject”.  
Pvalue > 0.05  The Pvalue is near the cutoff. It is considered as marginal  The hypothesis needs more attention. 
Examples Using Pvalue Formula
Example 1: A statistician is testing the hypothesis H0: μ = 120 using the approach of alternative hypothesis Hα: μ > 120 and assuming that α = 0.05. The sample values that he took are as n =40, σ = 32.17 and x̄ = 105.37. What is the conclusion for this hypothesis?
Solution:
We know that,
\(\sigma_{\bar{x}}=\dfrac{\sigma}{\sqrt{n}}\)
Now substitute the given values
\(\sigma_{\bar{x}}=\dfrac{32.17}{\sqrt{40}}=5.0865\)
As per the test static formula, we get
t = (105.37 – 120) / 5.0865
Therefore, t = 2.8762
Using the ZScore table, finding the value of P(t > 2.8762)
we get,
P (t < 2.8762) = P(t > 2.8762) = 0.003
Therefore,
If P(t > 2.8762) =1  0.003 =0.997
P value =0.997 > 0.05
As the value of p > 0.05, the null hypothesis is accepted.
Therefore, the null hypothesis is accepted.
Example 2: Pvalue is 0.3105. If the level of significance is 5%, find if we can reject the null hypothesis.
Solution: Looking at the Pvalue table, the pvalue of 0.3105 is greater than the level of significance of 0.05 (5%), we fail to reject the null hypothesis.
Example 3: Pvalue is 0.0219. If the level of significance is 5%, find if we can reject the null hypothesis.
Solution: Looking at the Pvalue table, the pvalue of 0.0219 is less than the level of significance of 0.05, we reject the null hypothesis.
FAQs on Pvalue Formula
What is Meant by Pvalue Formula?
The Pvalue formula is short for probability value. Pvalue defines the probability of getting a result that is either the same or more extreme than the other actual observations. The Pvalue represents the probability of occurrence of the given event. The formula to calculate the pvalue is: \(Z = \frac{\hat{p}p 0}{\sqrt{\frac{p 0(1p 0)}{n}}}\)
What is the Formula to Calculate the Pvalue?
The formula to calculate the Pvalue is:
\(Z = \frac{\hat{p}p 0}{\sqrt{\frac{p 0(1p 0)}{n}}}\)
Where,
 \(\hat{p}=\)Sample Proportion
 \(\mathrm{P0}=\) assumed population proportion in the null hypothesis
 N = sample size
What is the Pvalue Formula Table?
The Pvalue formula table is:
Pvalue  Description  Hypothesis Interpretation  
Pvalue ≤ 0.05 

Rejected  
Pvalue > 0.05 

Accepted or it “fails to reject”.  
Pvalue > 0.05  The Pvalue is near the cutoff. It is considered as marginal  The hypothesis needs more attention. 
Using the Pvalue Formula Table, Check if the Hypothesis is Rejected or not when the Pvalue is 0.354 with 5% Level of Significance.
Looking at the table, the pvalue of 0.354 is greater than the level of significance of 0.05 (5%), we fail to reject the null hypothesis.