Evaluate one sample means against target benchmarks. Get t scores, p values, and interval estimates. Built for coursework, quality checks, and research decisions today.
Enter raw sample data or enter summary statistics. If raw data is provided, the calculator will use it first.
This example shows a small sample that can be tested against a target mean of 10.
| Observation | Value |
|---|---|
| 1 | 11.2 |
| 2 | 9.8 |
| 3 | 10.9 |
| 4 | 12.1 |
| 5 | 11.4 |
| 6 | 10.7 |
| 7 | 9.9 |
| 8 | 11.6 |
The one mean t test checks whether a sample mean differs from a hypothesized population mean when the population standard deviation is unknown.
t = (x̄ - μ0) / (s / √n)
Degrees of freedom = n - 1
Confidence interval = x̄ ± tcritical × standard error
A one mean t test calculator helps you compare a sample mean with a known target value. It is a standard tool in statistics, research, quality control, and classroom work. You can use it when the population standard deviation is unknown. That is the usual real world case.
This calculator measures whether the observed sample mean is far enough from the hypothesized mean to be statistically meaningful. It uses the sample size, sample standard deviation, and standard error. The final output includes the t statistic, degrees of freedom, p value, and confidence interval.
The p value tells you how likely the sample result would be if the null hypothesis were true. A small p value suggests that the observed mean is unlikely under the stated assumption. That helps you decide whether to reject the null hypothesis. It does not prove a theory. It supports a decision rule.
Use this one sample t test calculator for test scores, production weights, waiting times, response values, survey metrics, and small experimental samples. It is especially useful when you only have one group and want to compare its average with a benchmark, claim, or expected value.
This page accepts either raw sample values or summary statistics. Raw data entry is helpful when you want quick analysis without computing the mean and sample standard deviation yourself. The calculator can derive those values automatically. That saves time and reduces manual entry mistakes.
The confidence interval gives a practical range for the unknown population mean. If the hypothesized mean falls outside a two sided interval, the result usually aligns with statistical significance at the same level. The test direction also matters. A left tailed test and a right tailed test answer different questions.
This calculator is designed for clear statistical work. It keeps the page simple, shows the result above the form, and includes exports for reporting. That makes it useful for students, teachers, analysts, and researchers who need a fast and readable one mean t test result.
A one mean t test compares a sample mean with a claimed or target population mean. It is used when the population standard deviation is unknown and the sample data is reasonably normal.
Use it when you have one sample and need to test whether its average differs from a reference value. It works for class exercises, experiments, audits, and performance checks.
Yes. Enter numbers separated by commas, spaces, or line breaks. The calculator will compute the sample mean, sample standard deviation, sample size, and test result automatically.
The p value measures how compatible your sample result is with the null hypothesis. A smaller p value means the sample mean is less likely under that hypothesis.
The null hypothesis states that the population mean equals the hypothesized mean. The alternative hypothesis says the population mean is different, greater, or smaller, based on your selection.
Degrees of freedom affect the t distribution shape and the critical value. In a one mean t test, the degrees of freedom equal the sample size minus one.
Yes. It reports a confidence interval using the selected significance level. The interval helps you judge the practical range of the population mean, not just significance.
The sample should be independent, and the data should be approximately normal, especially for small samples. Severe outliers can distort the test and lead to poor conclusions.
Important Note: All the Calculators listed in this site are for educational purpose only and we do not guarentee the accuracy of results. Please do consult with other sources as well.