T-Test Calculator

Determine if there is a statistically significant difference between means. Select your test type, enter your raw data, and instantly calculate the t-statistic and p-value.

How to use this calculator

1. Select your test type:
   • One-Sample: Compares a single sample to a known population mean.
   • Independent (Two-Sample): Compares the means of two independent, unrelated groups (this calculator uses Welch’s t-test, which does not assume equal variances).
   • Paired: Compares two sets of data from the same participants (e.g., pre-test and post-test scores).
2. Enter your data: Paste your raw data into the input boxes. For paired tests, ensure both datasets have the exact same number of values.
3. Set your parameters: Choose your significance level ($\alpha$) and whether you are running a one-tailed or two-tailed test. (If you aren’t sure, Two-tailed at an $\alpha = 0.05$ level is the standard default for most research).

Understanding Your Results

A t-test helps you determine if a difference in averages is real, or if it likely just happened by random chance.

• T-Statistic ($t$): The ratio of the difference between your groups to the variation within your groups. A larger t-score (positive or negative) indicates a larger difference between your samples.
• Degrees of Freedom ($df$): Roughly speaking, this is the number of independent pieces of information that went into calculating the estimate. It is tied to your sample size.
• P-Value: The probability of getting your exact results (or more extreme) if there was actually no real difference (the null hypothesis).
• Conclusion: If the p-value is less than your chosen significance level, you reject the null hypothesis and conclude that the difference is statistically significant.