1. What is P-value in Hypothesis Testing?

The p-value is the probability of obtaining test results at least as extreme as the observed results, assuming the null hypothesis is true. It helps determine the statistical significance of results.

2. How Does the Calculator Work?

The calculator uses the formula:

Where:

• \( test\_stat \) — The calculated test statistic from your hypothesis test
• \( df \) — Degrees of freedom for the test
• \( cdf \) — Cumulative distribution function for the appropriate distribution

Explanation: The calculator computes the area under the probability distribution curve from your test statistic to infinity.

3. Importance of P-value Calculation

Details: P-values are fundamental in hypothesis testing, helping researchers determine whether to reject the null hypothesis. A smaller p-value provides stronger evidence against the null hypothesis.

4. Using the Calculator

Tips: Enter your test statistic and degrees of freedom. The calculator will compute the one-tailed p-value. For two-tailed tests, double the result.

5. Frequently Asked Questions (FAQ)

Q1: What is a statistically significant p-value?
A: Typically, p-values less than 0.05 are considered statistically significant, but this threshold can vary by field.

Q2: How does degrees of freedom affect the p-value?
A: Higher degrees of freedom make the distribution more normal, affecting the p-value calculation.

Q3: What distribution does this calculator use?
A: The calculator uses the t-distribution, which is appropriate for most common hypothesis tests.

Q4: Can I use this for z-tests?
A: Yes, with large degrees of freedom (typically >30), the t-distribution approximates the normal distribution.

Q5: What if I need a two-tailed p-value?
A: Multiply the result by 2 for a two-tailed test.