BravoCalc

P-Value Calculator

Calculate statistical significance with our comprehensive p-value calculator. Supports multiple test types with detailed explanations and interpretations.

Statistical P-Value Calculator

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What is a P-Value?

A p-value is a statistical measure that helps determine the significance of your results. It represents the probability of obtaining test results at least as extreme as the observed results, assuming that the null hypothesis is correct.

Key Concepts

  • • P-value ≤ 0.05: Statistically significant
  • • P-value > 0.05: Not statistically significant
  • • Lower p-values indicate stronger evidence
  • • Always interpret in context of your study

Common Thresholds

  • • α = 0.05 (5%): Standard significance level
  • • α = 0.01 (1%): High significance level
  • • α = 0.10 (10%): Exploratory research
  • • α = 0.001 (0.1%): Very high significance

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Types of Statistical Tests

T-Test

Compare means when population standard deviation is unknown

  • • One-sample t-test
  • • Two-sample t-test
  • • Paired t-test

Z-Test

Compare means when population standard deviation is known

  • • One-sample z-test
  • • Two-sample z-test
  • • Proportion z-test

Chi-Square

Test relationships between categorical variables

  • • Goodness of fit
  • • Independence test
  • • Homogeneity test

F-Test

Compare variances or test multiple means

  • • ANOVA F-test
  • • Variance ratio test
  • • Regression F-test

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Hypothesis Testing Process

1

State Hypotheses

Define null (H₀) and alternative (H₁) hypotheses

2

Choose α Level

Set significance level (typically 0.05)

3

Calculate Test Statistic

Compute appropriate test statistic

4

Find P-Value

Calculate probability of observed results

5

Make Decision

Compare p-value to α and conclude

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Interpreting P-Values

P-value ≤ 0.001 (Very Strong Evidence)

Extremely strong evidence against the null hypothesis. Results are highly statistically significant.

0.001 < P-value ≤ 0.01 (Strong Evidence)

Strong evidence against the null hypothesis. Results are statistically significant.

0.01 < P-value ≤ 0.05 (Moderate Evidence)

Moderate evidence against the null hypothesis. Results are statistically significant at α = 0.05.

0.05 < P-value ≤ 0.10 (Weak Evidence)

Weak evidence against the null hypothesis. Results are marginally significant.

P-value > 0.10 (No Evidence)

Little or no evidence against the null hypothesis. Results are not statistically significant.

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Common Mistakes to Avoid

❌ P-hacking

Manipulating data or analysis to achieve significant p-values

❌ Multiple Comparisons

Not adjusting for multiple tests increases Type I error rate

❌ Misinterpreting Non-significance

P > 0.05 doesn't prove the null hypothesis is true

✅ Pre-specify Analysis

Plan your statistical analysis before collecting data

✅ Use Corrections

Apply Bonferroni or FDR corrections for multiple tests

✅ Report Effect Sizes

Include confidence intervals and effect size measures