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)

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.

How to Use This Tool

Select your test type — choose from T-Test, Z-Test (proportions), Chi-Square, or Correlation depending on your data and hypothesis.
Configure the test — pick one-sample, two-sample, or paired variants, and set the significance level (alpha) and tail direction.
Enter your sample statistics — input values such as sample mean, standard deviation, sample size, or observed proportions.
View your results — get the p-value, test statistic, effect size (Cohen's d, Cramer's V, etc.), confidence interval, and a plain-language interpretation.
Save or copy results — save calculations to your history or copy the summary to your clipboard.

Common Use Cases

Is the difference between my two groups statistically significant? Use the two-sample T-Test to compare means and get a p-value with effect size.
Did my treatment have a real effect or was it chance? Run a one-sample or paired T-Test against your baseline to determine significance.
Is my survey response rate different from the industry average? The Z-Test for proportions compares your observed proportion to a hypothesized value.
Are two categorical variables related? Enter your contingency table in the Chi-Square test to check for independence between categories.
Is my correlation coefficient statistically meaningful? The Correlation test determines whether your observed r-value is significantly different from zero.