P-Value Calculator Information
What is a P-Value?
A p-value is the probability of obtaining results at least as extreme as those observed, assuming the null hypothesis is true. It helps you decide whether to reject the null hypothesis in hypothesis testing.
- p-value = Probability of observing the data or more extreme results
- H₀ = Null hypothesis (assumption being tested)
- P = Probability function
Example: p = 0.03
p = 0.03 < 0.05, so reject the null hypothesis
Why Use P-Values?
- Statistics: Test hypotheses and make data-driven decisions
- Research: Report significance of findings
- Science: Communicate reliability of results
- Business: Analyze experiments and A/B tests
Tips for Interpreting P-Values
- Threshold: Common cutoff is 0.05 (5%)
- Smaller is Stronger: Lower p-values mean stronger evidence against H₀
- Not Proof: A small p-value does not prove the alternative hypothesis
- Context Matters: Consider effect size, sample size, and study design
Frequently Asked Questions (FAQ)
A: It is the probability of seeing your data (or more extreme) if the null hypothesis is true.
A: Typically, p < 0.05 is considered significant, but this can vary by field.
A: P-values are used for many tests, but always check assumptions and context.
A: It is right at the threshold; interpretation may depend on context.
A: No, it only suggests evidence against the null hypothesis, not proof.
Important Disclaimers
Disclaimer: This calculator provides estimates for educational purposes only. Statistical calculations are based on standard statistical methods and assumptions.
For critical applications such as scientific research, clinical trials, or business decisions, always verify results with professional statistical software and consult with qualified statisticians.
This calculator is not a substitute for professional statistical analysis tools or expert statistical consultation. Always use appropriate significance levels and consider the context of your analysis.