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Significance Test Calculator (Two-Sample t-Test)

Run an independent two-sample t-test (Welch or Student) by entering each group's raw data, or just the mean, standard deviation and sample size. Get the t-statistic, degrees of freedom and approximate p-value, with a quick significant/not-significant verdict at the 5% level.

Input

Input method

Test type

Result

t-statistic (test statistic)

3.881

Significant difference (5% level)

Degrees of freedom (df)

9.99

Approx. p-value

0.0031

Mean difference (A−B)

11.833

Summary statistics by group

GroupSample size nMeanStd. deviationUnbiased variance
Group A683.3335.35428.667
Group B671.55.20627.1

Note: the p-value is an approximation of the two-tailed probability from the t-distribution. A difference is flagged as significant when p is below 0.05. This is for reference only; use dedicated statistical software for formal analysis.

How it works

  • This tool gives a quick verdict on whether two group means differ statistically, using an independent two-sample t-test. Enter raw data directly (separated by line breaks, commas or spaces), or supply each group's mean, standard deviation and sample size.
  • "Welch" does not assume equal variances between the two groups and works well even when sample sizes or spreads differ. "Student" assumes equal variances and pools them in the calculation. If in doubt, Welch is the safer choice.
  • Variance and standard deviation use unbiased estimates (the sum of squared deviations divided by n−1 rather than n). When entering summary statistics, also provide the unbiased standard deviation.
  • The p-value is an approximation of the two-tailed probability derived from the calculated t-statistic and degrees of freedom on the t-distribution. By convention, a difference is reported as significant at the 5% level when p is below 0.05.
  • Each group needs at least two values. The result is a simplified calculation for learning and reference; it does not check normality or outliers or evaluate effect size or confidence intervals. For papers or professional work, use dedicated statistical software.