t-Test Calculator (Biology)

A t-test is a statistical method used in biology to determine whether the means of two groups — such as a control and treatment group — are significantly different from each other. Select your type of t-Test (unpaired, Welch's, or paired) and significance level, then enter each group's sample mean, sample size, and standard deviation into the t-Test Calculator. Results include the t-statistic, p-value, degrees of freedom, mean difference, 95% confidence interval, Cohen's d effect size, and a plain-language significance verdict. Also try the Power Analysis Calculator (Biology).

Results

t-Statistic

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p-value

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Degrees of Freedom

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Mean Difference

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95% CI Lower

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95% CI Upper

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Cohen's d (Effect Size)

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Result

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Results Table

Frequently Asked Questions

What is a t-test and when should I use it in biology?

A t-test compares the means of two groups to determine if they are statistically different. In biology, use it to compare treatment vs control groups, different species measurements, or pre/post treatment data when you have continuous numerical data. See also our Correlation Coefficient Calculator (Biology).

What's the difference between unpaired and paired t-tests?

Unpaired t-tests compare two independent groups (e.g., males vs females). Paired t-tests compare the same subjects before and after treatment (e.g., blood pressure before and after medication). Choose based on your experimental design.

What does the p-value tell me about my biological data?

The p-value indicates the probability of observing your results if there's no real difference between groups. If p < 0.05, your results are statistically significant, meaning the difference is likely real, not due to chance.

How do I interpret Cohen's d effect size?

Cohen's d measures the magnitude of difference between groups. Small effect: d = 0.2, Medium: d = 0.5, Large: d = 0.8. A large effect size means the biological difference is substantial, even if statistically significant. You might also find our calculate Confidence Interval (Biology) useful.

What assumptions must my biological data meet for t-tests?

Your data should be approximately normally distributed, observations should be independent, and for unpaired t-tests, both groups should have similar variances. Small departures from normality are usually acceptable with sample sizes > 15.

When should I use Welch's t-test instead of standard t-test?

Use Welch's t-test when your two groups have unequal variances (one group has much more spread than the other). It's more robust and doesn't assume equal variances like the standard unpaired t-test.

What sample size do I need for reliable t-test results?

Generally, n ≥ 15 per group provides reasonable results. Smaller samples (n < 10) require very normal data. For detecting small biological effects, you may need 30+ subjects per group for adequate statistical power.

How do I report t-test results in my biology research?

Report the t-statistic, degrees of freedom, p-value, and effect size. Example: 't(46) = 2.34, p = 0.023, d = 0.68'. Include means ± standard deviations for both groups and the 95% confidence interval for the difference. Check out our use the Sample Size Calculator (Biology) as well.