What is a p-value and what does it mean?

A p-value is the probability of obtaining results at least as extreme as the observed results, assuming the null hypothesis is true. A small p-value (typically ≤ 0.05) suggests the observed data is unlikely under the null hypothesis, leading to its rejection.

Is this p-value calculator really free with no signup?

Yes! This calculator is completely free with no signup, registration, or account required. Simply select your test type, enter your data, and get instant results.

When should I use a one-tailed vs two-tailed test?

Use a one-tailed test when you have a specific directional hypothesis. Use a two-tailed test (recommended for most cases) when you want to detect differences in either direction.

What is effect size and why does it matter?

Effect size measures the magnitude of a difference or relationship, independent of sample size. While p-values tell you if an effect exists, effect size tells you how large it is.

Free Online p-Value Calculator (No Signup)

Calculator Settings

Test Configuration

T-Test Type

Tail Type

Two-tailed Left-tailed Right-tailed

Significance Level (α)

Sample Data

Hypothesized Mean (μ₀)

Sample Mean (x̄)

Sample Std Dev (s)

Sample Size (n)

Sample 1 (Group A)

Mean (x̄₁)

Std Dev (s₁)

Size (n₁)

Sample 2 (Group B)

Mean (x̄₂)

Std Dev (s₂)

Size (n₂)

Paired Differences

Mean Difference (d̄)

Std Dev of Diff (s_d)

Number of Pairs (n)

Test Configuration

Z-Test Type

Tail Type

Two-tailed Left-tailed Right-tailed

Significance Level (α)

Sample Data

Hypothesized Proportion (p₀)

Successes (x)

Sample Size (n)

Sample 1

Successes (x₁)

Sample Size (n₁)

Sample 2

Successes (x₂)

Sample Size (n₂)

Test Configuration

Significance Level (α)

Contingency Table (2×2)

Row 1 (e.g., Treatment Group)

Row 2 (e.g., Control Group)

Test Configuration

Tail Type

Two-tailed One-tailed

Significance Level (α)

Correlation Data

Correlation (r)

Sample Size (n)

Results

Select a test type, enter your data, and click "Calculate" to see your results.

✓

Statistically Significant

at α = 0.05 level

Effect Size: Medium d = 0.52

NegligibleSmallMediumLarge

📊 Interpretation

Calculation Details

Calculation History

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How to Use This Free p-Value Calculator

Select the appropriate test type based on your data and hypothesis, enter your sample statistics, and get instant results with effect sizes and interpretations.

T-Test

Compare means between groups or against a hypothesized value. Use for continuous data with approximately normal distribution.

Z-Test (Proportions)

Test hypotheses about proportions. Use when comparing an observed proportion to a known value, or comparing proportions between two groups.

Chi-Square Test

Test for independence between categorical variables. Enter your contingency table to determine if there's a significant association.

Correlation Test

Test whether a correlation coefficient is significantly different from zero. Enter your observed correlation and sample size.