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Statistics

One-Sample t-Test Calculator

Compute one-sample t-statistic from sample values and hypothesized mean.

Last validated: 2026-02-14

One-Sample t-Test Calculator tests whether a sample mean differs from a hypothesized reference mean. The null hypothesis states that the population mean equals the reference value, while the alternative hypothesis states that it is different, greater, or smaller depending on the test design. The t-statistic compares the observed mean difference with the standard error of the mean, and degrees of freedom usually equal sample size minus one. The p-value measures how unusual the observed result would be if the null hypothesis were true; it is not the probability that the null hypothesis is true. This test is useful for small-sample inference when population variance is unknown, but it assumes independent observations and roughly appropriate distributional behavior.

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Input Pattern

Enter values in the left panel, keep units explicit, run the calculation, then copy or share the result. Invalid fields are highlighted immediately.

One-Sample t-Test Inputs

Result

n: 7

Mean: 13.714286

Std dev: 1.799471

t-statistic: 1.050210

df: 6

How to use this tool

  1. Enter Sample values, Hypothesized mean (mu0) for the one sample t test calculator, keeping units, dates, or text format consistent with the form labels.
  2. Confirm sample size, ordering, and distribution assumptions before relying on the calculated result.
  3. Click "Run the tool" and review One-Sample t-Test Inputs, Result for the primary output.
  4. Check the statistical assumptions and sample context before using the result in a report or decision.

Worked Example

Auto-generated from the tool's current default or entered inputs.

Example Inputs

  • Values: 12, 15, 14, 13, 16, 11, 15
  • Mu0: 13.0
  • N: 7
  • Std dev: 1.7994708216848745
  • Stderr: 0.6801360408136047
  • T statistic: 1.0502100630210063
  • Df: 6

Expected Outputs

  • Mu0: 13
  • N: 7
  • Mean: 13.714286
  • Std dev: 1.799471

Interpretation

Confidence and limitations

Formula References

Assumptions

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