In statistical hypothesis testing, the P value is a crucial metric that helps researchers assess the evidence against a null hypothesis. Calculating P values aids in making informed decisions about the statistical significance of results.

### Formula

The P value is computed based on various statistical distributions, such as the t-distribution or chi-square distribution, depending on the test being conducted. It represents the probability of obtaining results as extreme or more extreme than the observed results under the assumption that the null hypothesis is true.

### How to Use

- Enter the observed value in the designated field.
- Input the expected value.
- Specify the degrees of freedom for your test.
- Click the “Calculate” button to obtain the P value.

### Example

Suppose you conducted a chi-square test with observed value = 25, expected value = 20, and degrees of freedom = 3. After inputting these values, click “Calculate” to find the P value.

### FAQs

**Q: What is a P value?**A: The P value is a measure indicating the probability of obtaining observed results under the assumption that the null hypothesis is true.**Q: How is the P value interpreted?**A: A smaller P value suggests stronger evidence against the null hypothesis.**Q: Can the P value be greater than 1?**A: No, P values are probabilities and fall between 0 and 1.**Q: When is a P value considered significant?**A: Typically, a P value less than 0.05 is considered statistically significant.**Q: What is the null hypothesis?**A: The null hypothesis posits no effect or no difference in the population.

### Conclusion

Understanding how to calculate P values is essential for researchers and statisticians to draw meaningful conclusions from their data. This calculator provides a quick and efficient way to determine the P value for various statistical tests.