What is the difference between one-sample and two-sample t-tests?

A one-sample t-test compares a single group mean to a known value. A two-sample t-test compares the means of two independent groups against each other.

Does this assume equal variances?

No. This calculator uses Welch's t-test, which adjusts the degrees of freedom to account for potentially unequal variances between the two groups. It is more robust than Student's t-test.

What does the p-value mean?

The p-value is the probability of observing a difference at least as large as the one in your data if the null hypothesis (no true difference) were true. A small p-value (e.g., < 0.05) suggests the difference is unlikely to be due to chance.

What significance level should I use?

The most common threshold is 0.05 (5%). Use 0.01 for stricter tests (medical/safety studies) or 0.10 for more exploratory analysis. The appropriate level depends on the context and cost of false positives.

How many data points do I need?

You need at least 2 values per group. For reliable results, at least 10–30 observations per group is recommended. Very small samples produce wide confidence intervals and low power.

Is this a one-tailed or two-tailed test?

This calculator performs a two-tailed test, which checks for a difference in either direction. Divide the displayed p-value by 2 if you have a one-directional hypothesis.

Two Sample T-Test Calculator

Enter data for two groups to compute the t-statistic, p-value, and determine if the difference in means is statistically significant.

Group 1 Data

— values

Group 2 Data

— values

Significance Level (alpha)

Descriptive Statistics

Statistic	Group 1	Group 2

Enter data for both groups and click Run T-Test to see results.

Summary

The two-sample t-test (also called the independent samples t-test) compares the means of two unrelated groups to determine whether there is a statistically significant difference between them. You provide each group's data values, and the calculator computes the t-statistic and p-value using Welch's t-test, which does not assume equal variances. A p-value below your chosen significance level (commonly 0.05) indicates a statistically significant difference.

How it works

Enter the data values for Group 1, one number per line or comma-separated.
Enter the data values for Group 2 in the same format.
Select your desired significance level (alpha) — commonly 0.05.
Click "Run T-Test" to compute the t-statistic, degrees of freedom, and two-tailed p-value.
The result shows whether to reject the null hypothesis at your chosen alpha.
Descriptive statistics (mean, variance, standard deviation) for each group are also displayed.

Use cases

Compare test scores between two classroom groups to check if a teaching method made a difference.
Evaluate whether a new drug produces a significantly different outcome than a placebo.
Determine if conversion rates differ between two A/B test variants.
Assess whether salary data differs between two departments.
Validate experiment results in scientific research and data analysis.
Check if a product change measurably improves or harms a key metric.

Frequently Asked Questions

Last updated: 2026-05-29 · Reviewed by Nham Vu