Use 1-sample hypothesis tests to compare one sample with a
hypothesized value.

To add output from a 1-sample hypothesis test, go to Add and complete a form.

Use a 1 proportion test to estimate a binomial population
proportion and to compare the proportion to a target value or a reference
value.

For example, you can test whether a new setting significantly changes the proportion defective. To see an example, go to Minitab Help: Example of 1 Proportion.

Your data must contain only two categories, such as pass/fail. For details, go to Minitab Help: Data considerations for 1 Proportion.

Use a 1-sample t-test to estimate the mean of a population and to
compare it to a target value or a reference value when you do not know the
standard deviation of the population.

For example, you can test whether the mean output from the controlled improved process is different from the pre-project mean. To see an example, go to Minitab Help: Example of 1-Sample t.

The data must be continuous and reasonably normal. A 1-sample t-test is robust to violations of the normality assumption, especially if the sample size is large (n > 25). For more details, go to Minitab Help: Data considerations for 1-Sample t.

Use a 1-sample
Wilcoxon test to estimate the population median and
to compare it to a target value or a reference value.
This test is an alternative to the 1-sample t-test and is used
when the data are not reasonably normal.

For example, you can test whether the mean output from the controlled improved process is different from the pre-project mean. To see an example, go to Minitab Help: Example of 1-Sample Wilcoxon.

Your data must be a continuous value for Y (output). The data should come from a symmetric distribution, such as the uniform or Cauchy distributions. If your data do not come from a symmetric distribution, use a 1-sample sign test. For more details, go to Minitab Help: Data considerations for 1-Sample Wilcoxon.

Use a 1 variance test to estimate either the variance or the
standard deviation of a population and to compare that value to a target value
or a reference value.

For example, a quality analyst uses a 1 variance test to determine whether the variance of the moisture content in a shipment of unprocessed lumber is too high. To see an example, go to Minitab Help: Example of 1 Variance.

Your data must be continuous Y (output) values. For more details, go to Minitab Help: Data considerations for 1 Variance.

Use a 1-sample sign test to estimate the population median and to
compare it to a target value or a reference value.
This test is an alternative to the 1-sample t-test and is used
when the data are not reasonably normal.

For example, you can test whether the mean output from the controlled improved process is different from the pre-project mean. To see an example, go to Minitab Help: Example of 1-Sample Sign.

Your data must be a continuous value for Y (output). The 1-sample sign
test is not as powerful as other alternatives.

- Use the 1-sample t-test when the data are reasonably normal (or the sample size is large).
- Use the 1-sample Wilcoxon test as an alternative to the 1-sample t-test as long as the data are reasonably symmetric.
- Use the 1-sample sign test as a last resort.