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T-Test Calculator

One-sample t-test, with what a p value does not mean.

Work out T-Test. One-sample t-test, with what a p value does not mean. Free, with no account and nothing to download.

Written and maintained by Mohit PatelLast checked August 4, 2026How we build these

A p value is not the probability the null hypothesis is false, and a non-significant result is not evidence of no effect.

t statistic

2.5

p = 0.01965 · 24 degrees of freedom

t statistic2.5
p value (two-tailed)0.019654
Degrees of freedom24
Significant?Yes
ConclusionReject the null hypothesis at α = 0.05 — the difference is unlikely to be chance alone

A one-sample two-tailed t-test: how far the sample mean sits from the hypothesised one, measured in standard errors. The p value is the probability of seeing a difference this large or larger if the null hypothesis were true. A p value is not the probability that the null hypothesis is false, and "not significant" is not evidence of no effect — it may only mean the sample was too small to detect one. Both misreadings are extremely common and both change what you would do next. Statistical significance also says nothing about size. With a large enough sample a trivial difference becomes significant, which is why the effect size matters more than the p value for any practical decision.

How the T-Test Calculator works

Enter a sample mean, a hypothesised mean, the sample standard deviation and the sample size for the t statistic and a two-tailed p value. The page is explicit about the two misreadings of a p value that change what you would do next.

Also known as: one sample t test calculator · p value calculator · t statistic calculator · hypothesis test calculator

Frequently asked questions

What does a p value actually mean?

The probability of seeing a difference at least this large if the null hypothesis were true. It is not the probability that the null hypothesis is false, and treating it as such is the commonest error in applied statistics.

Does a non-significant result mean there is no effect?

No. It means this sample did not provide enough evidence to detect one, which may simply mean the sample was too small. Absence of evidence is not evidence of absence.

What are degrees of freedom?

The sample size minus one for a one-sample test. Once the mean and all but one value are known, the last is determined — so only n−1 values are free to vary.

Is a significant result an important one?

Not necessarily. With a large enough sample a trivial difference becomes statistically significant. Effect size matters far more than the p value for any practical decision.

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