GraphPad T Test Calculator

Calculator Form

Test type

Alternative hypothesis

Unpaired variance method

Confidence level

Null mean or null difference

Group A raw data

Group B raw data

Group A sample size

Group A mean

Group A sample SD

Group B sample size

Group B mean

Group B sample SD

Example Data Table

Example	Group A	Group B	Suggested test	Null value
Independent groups	14.2, 15.1, 13.8, 16.4, 15.9	12.7, 13.1, 11.9, 14.0, 13.4	Welch unpaired	0
Before and after	82, 79, 88, 91, 85	78, 77, 84, 87, 82	Paired	0
Target mean	102, 98, 105, 101, 99	Not used	One sample	100

Formula Used

One sample and paired tests: t = (mean difference - null value) / (sample standard deviation / square root of n). Degrees of freedom equal n - 1.

Welch unpaired test: t = ((mean A - mean B) - null difference) / square root of ((SD A squared / n A) + (SD B squared / n B)). Degrees of freedom use the Welch Satterthwaite approximation.

Pooled unpaired test: t = ((mean A - mean B) - null difference) / (pooled SD times square root of (1 / n A + 1 / n B)). Degrees of freedom equal n A + n B - 2.

Confidence interval: mean difference plus or minus the critical t value multiplied by standard error.

How to Use This Calculator

Select the test type that matches your study design.
Choose the tail direction before reading results.
Enter raw data or summary values.
Set the null mean or null difference.
Press calculate to display results below the header.
Use CSV or PDF buttons to save the same result.

About the GraphPad T Test Calculator

A t test compares means. It can test one sample. It can compare two independent groups. It can also compare matched pairs. This calculator keeps those choices in one place. It accepts raw observations and summary values. That flexibility helps students, analysts, and researchers. It also helps when only published summaries are available.

Why This Calculator Helps

Some tools return only a t statistic. This version gives more detail. You get degrees of freedom. You also get standard error. The output includes confidence intervals and effect size. Each result supports stronger interpretation. The method note explains the selected test. The conclusion line describes the p value. It still cannot replace study judgment.

Understanding Inputs

Enter raw data with commas, spaces, or new lines. Use one row of numbers for each group. Paired tests need equal list lengths. Each first value matches the first second value. Summary mode needs sample size, mean, and standard deviation. Use sample standard deviation. Do not use population spread. For one sample tests, enter the hypothesized mean.

Reading the Results

The t statistic measures distance from the null value. It divides the observed difference by standard error. Large absolute values create smaller p values. A p value estimates surprise under the null model. The confidence interval gives a likely range. If it excludes zero, the difference is notable. Effect size reports practical magnitude. Cohen values are guidelines, not laws.

Best Practice Notes

Use two tailed testing when either direction matters. Use one tailed testing only with prior planning. Welch testing is safer for unequal variances. Pooled testing assumes similar variances. Paired testing fits before and after records. One sample testing fits a target value. Always inspect data quality. Check missing values and outliers. Report assumptions with the final result.

Exporting Work

CSV downloads suit spreadsheets and audit trails. PDF downloads suit quick sharing. The example table shows realistic inputs. It helps users verify formatting. Save results with the project name. Then compare runs when assumptions change.

Accuracy Tips

Use enough data for stable estimates. Very small samples are fragile. Record units before entering values. Keep group labels clear. Recheck copied numbers. Save exports beside original data. Review methods before reporting.

FAQs

What is a t test?

A t test compares means while accounting for sample variation. It is useful when data are numeric and sample standard deviations are estimated from the data.

When should I use Welch testing?

Use Welch testing for independent groups when variances may differ. It is often safer than pooled testing because it does not require equal group variance.

When should I use a paired test?

Use a paired test when each value in one list matches one value in the other list. Common examples include before and after measurements.

What does the p value mean?

The p value estimates how unusual the observed t statistic is under the null hypothesis. Smaller values give stronger evidence against that null model.

What is Cohen d?

Cohen d is an effect size. It expresses the mean difference in standard deviation units. It helps judge practical importance beyond statistical significance.

Can I enter summary data?

Yes. Choose a summary test type. Enter sample size, mean, and sample standard deviation. Summary mode is useful for published studies.

What confidence level should I use?

A 95 percent confidence level is common. Use another level when your class, field, or reporting rule requires it.

Are results exact for every case?

The calculator uses standard t distribution methods and numerical approximations. Results are suitable for routine checks, but critical research should use verified statistical software.