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One-Sample T Statistic Calculator
Compute t = (sample mean−reference mean)/(sample standard deviation/√n).
Your results will appear here.
Three steps. That’s it.
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Calculate one-sample t statistic online
Compute t = (sample mean−reference mean)/(sample standard deviation/√n). Use this for the specific transformation described above. Start with the fixed sample and compare its result before replacing it with your own representative input.
How to use it
Enter a value or text in the format shown in the example. Set reference mean. Choose Calculate. Review the output, then copy or download it.
Options and example settings
Worked examples
Use this for the specific transformation described above. Start with the fixed sample and compare its result before replacing it with your own representative input.
Reproducible worked example
Settings: Reference mean: 10
Input:
10,11,12,13,14
With the input and settings above, the tool produces:
Output:
{
"t": 2.82842712474619,
"degreesOfFreedom": 4,
"sampleMean": 12
}For this input, “t” is 2.82842712474619; “degreesOfFreedom” is 4; “sampleMean” is 12. These are the named fields in the example output.
Limitations and common mistakes
- Statistic only; no p-value or hypothesis conclusion. Sampling and normality assumptions require separate assessment.
- Combined input is bounded to 150,000 characters; output text is bounded to 1.2 million characters. Some algorithms impose smaller limits, stated in their error messages.
Frequently asked questions
What format should I enter?
Enter a value or text in the format shown in the example. The worked example shows the supported structure and actual output.
How can I compute one-sample t statistic online?
Enter a value or text in the format shown in the example. Set reference mean. Choose Calculate. Review the output, then copy or download it.
Where is my input processed?
The bundled tool processes input in your browser. It does not upload tool input to a conversion service. Other site plugins, analytics, advertising and browser extensions may have separate behavior.
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