T-Test Calculator

Calculate t-statistics, p-values, and determine statistical significance for one-sample, independent, and paired t-tests

Home Categories Math T-Test Calculator

t = (x̄ - μ₀) / (s / √n)

Basic T-Test Formula

Group 1

Group 2

Format: before,after pairs separated by semicolons

Quick Examples

t-Statistic

Significance Scale

Highly Significant Significant Marginal Not Significant

t-Statistic

Degrees of Freedom

p-Value

Critical Value

±

Effect Size (Cohen's d)

Confidence Interval

[, ]

Interpretation

Reject the null hypothesis. The p-value () is less than your significance level (α = ).

Fail to reject the null hypothesis. The p-value () is greater than or equal to your significance level (α = ).

The absolute t-statistic (|t| = ) exceeds the critical value ().

The absolute t-statistic (|t| = ) does not exceed the critical value ().

Critical Values Reference (Two-Tailed)

df α = 0.10 α = 0.05 α = 0.01

If you like this calculator

Please help us simply by sharing it. It will help us a lot!

Share this Calculator

About T-Test Calculator

What is a T-Test?

T-tests are statistical hypothesis tests used to compare means and determine if there is a statistically significant difference between groups or between a sample and a population.

Types of T-Tests

1. One-Sample T-Test

Compares a sample mean to a known or hypothesized population mean.

Formula: t = (x̄ - μ) / (s / √n)

Use when: You want to test if your sample differs from a known value.

2. Independent Samples T-Test (Two-Sample)

Compares the means of two independent groups.

Formula (Welch's): t = (x̄₁ - x̄₂) / √(s₁²/n₁ + s₂²/n₂)

Use when: Comparing two separate groups (e.g., treatment vs. control).

3. Paired Samples T-Test

Compares two related measurements from the same group.

Formula: t = d̄ / (sᵈ / √n)

Use when: You have before/after measurements or matched pairs.

Key Concepts

Term Description
t-statistic Measures how many standard errors the sample mean is from the hypothesized mean
Degrees of Freedom (df) n-1 for one-sample/paired, complex formula for independent
p-value Probability of getting results at least as extreme, assuming null hypothesis is true
Significance Level (α) Threshold for rejecting null hypothesis (usually 0.05)

Interpretation Guidelines

  • p < 0.01: Highly significant - very strong evidence against null hypothesis
  • p < 0.05: Significant - sufficient evidence to reject null hypothesis
  • p < 0.10: Marginally significant - weak evidence
  • p ≥ 0.10: Not significant - insufficient evidence to reject null hypothesis

Assumptions

  1. Normality: Data should be approximately normally distributed
  2. Independence: Observations should be independent (except for paired test)
  3. Equal Variances: For pooled t-test (Welch's t-test relaxes this assumption)

Note: This calculator uses Welch's t-test for independent samples, which doesn't assume equal variances.