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P-Value Calculator - Free Statistical Significance Calculator

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P-Value Calculator

Calculate p-values from test statistics to determine statistical significance. Supports z-tests, t-tests, chi-square tests, and F-tests.

Z-Test P-Value

Common Critical Values

α = 0.10
z = ±1.645
α = 0.05
z = ±1.96
α = 0.01
z = ±2.576

How to use this calculator

📈 How to Use This Calculator

  1. Select your test type: Z-test, T-test, Chi-square, or F-test
  2. Enter your test statistic value
  3. Provide degrees of freedom (for t, chi-square, and F tests)
  4. Choose the test direction (one-tailed or two-tailed)
  5. Click calculate to get the p-value and interpretation

📐 Understanding P-Values

What is a P-Value?

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

Common Significance Levels (α)

  • 0.10: Marginally significant (90% confidence)
  • 0.05: Statistically significant (95% confidence)
  • 0.01: Highly significant (99% confidence)
  • 0.001: Extremely significant (99.9% confidence)

Decision Rule

If p-value ≤ α: Reject the null hypothesis
If p-value > α: Fail to reject the null hypothesis

🌟 Test Types Guide

Z-Test

Used when population standard deviation is known or sample size is large (n > 30)

T-Test

Used for small samples when population standard deviation is unknown

Chi-Square Test

Used for categorical data, goodness of fit, or independence tests

F-Test

Used for comparing variances or in ANOVA

💡 Important Considerations

  • • P-values do not measure the size or importance of an effect
  • • Statistical significance does not imply practical significance
  • • Multiple testing requires adjustment (e.g., Bonferroni correction)
  • • Consider confidence intervals alongside p-values
  • • Pre-specify your significance level before analysis
  • • Report exact p-values rather than just "p < 0.05"

⚠️ Common Misinterpretations

  • • P-value is NOT the probability that the null hypothesis is true
  • • P-value is NOT the probability of making a Type I error
  • • A non-significant result does NOT prove the null hypothesis
  • • P = 0.051 is not fundamentally different from P = 0.049
  • • Small p-values can occur with trivial effects in large samples

About this calculator

Calculate p-values from test statistics for z-tests, t-tests, chi-square, and F-tests. Determine statistical significance easily.

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