Which t-test should I use?

Use the one-sample t-test when comparing a sample mean to a known reference value. Use the independent two-sample t-test when comparing means from two separate, unrelated groups. Use the paired t-test when each observation in group 1 is directly matched to one in group 2 (e.g., before/after measurements on the same subjects).

What p-value is considered statistically significant?

By convention, a p-value below 0.05 is considered statistically significant at the 5% level, meaning there is less than a 5% chance of observing such a result if the null hypothesis were true. This tool highlights results below 0.05, but the appropriate threshold depends on your field and study design.

Does this tool assume equal variances for two-sample tests?

No. The two-sample test uses Welch's t-test, which does not assume equal variances and is more robust than the pooled (Student's) t-test when group variances or sample sizes differ.

What is the degrees of freedom?

Degrees of freedom (df) represent the number of independent values in the calculation. For one-sample and paired tests, df = n − 1. For Welch's two-sample test, df is estimated using the Welch–Satterthwaite equation and may be non-integer.

Is my data sent to a server?

No. All calculations run entirely in your browser using JavaScript. No data is transmitted or stored.

What is a two-tailed p-value?

A two-tailed test checks whether the means differ in either direction (greater or less). This tool always reports the two-tailed p-value, which is the most conservative and most commonly reported form in research.

T Test Calculator

Name: T Test Calculator
Availability: InStock
Author: Nham Vu

Calculate the t-statistic and p-value for one-sample, two-sample, or paired t-tests using raw data or summary statistics.

Test Type

Input mode:

Group 1 data

Group 2 data

Hypothesized mean (H₀: μ =)

Enter your data and click Calculate

Results will appear here

t-statistic

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Degrees of Freedom

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p-value (2-tailed)

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Sample Statistics

Group	n	Mean	Std Dev	Std Error

Formula used

Summary

Calculate the t-statistic and p-value for one-sample, two-sample, or paired t-tests using raw data or summary statistics.

How it works

Select the test type: one-sample, two-sample (independent), or paired.
Enter your data as comma- or space-separated numbers, or switch to summary statistics mode.
For one-sample tests, set the hypothesized mean (H₀); for two-sample tests, paste a second data set.
Click Calculate to compute the t-statistic and degrees of freedom.
The tool looks up the p-value using a JavaScript implementation of the Student's t-distribution and reports whether the result is statistically significant at α = 0.05.

Use cases

Determine whether a product's average weight differs from the labelled value.
Compare exam scores between two student groups before and after an intervention.
Analyze before-and-after blood pressure readings in a clinical trial.
Validate A/B test results by checking if two conversion rate samples differ significantly.
Quickly verify homework or statistics course assignments.
Check whether a sample mean deviates from a quality-control threshold.
Perform preliminary data analysis before running more complex ANOVA tests.
Teach students the relationship between t-statistic, degrees of freedom, and p-value.

Frequently Asked Questions

Last updated: 2026-06-10 · Reviewed by Nham Vu