### Parametric Hypothesis Tests

Parametric Hypothesis tests are frequently used to measure the quality of sample parameters or to test whether estimates on a given parameter are equal for two samples.

Parametric Hypothesis tests set up a null hypothesis against an alternative hypothesis, testing, for instance, whether or not the population mean is equal to a certain value, and then using appropriate statistics to calculate the probability that the null hypothesis is true. You can then reject or accept the null hypothesis based on the calculated probability.

Origin provides the following Parametric Hypothesis Tests:

#### One-Sample T-Test

The one-sample student's t-test compares the mean of a sample to a specified value.

#### One-Sample Test for Variances PRO

This function performs a chi-square test to compare the variance of a sample to a known value.

#### One-Sample Proportion Test PRO

The tool uses two tests to determine whether the observed proportion is equal to a pre-specified proportion.

• Z-Test
• Fisher's Exact Test

### Pair-Sample T-Test

The Paired-Sample t-Test is a parametric hypothesis test that enables you to test whether the means of paired (or related, matched) samples are equal or differ by a given value.

The term paired means that there are two measurements taken on the same subject or there is one measurement taken on a pair of subjects.

#### Two-Sample T-Test

The two-sample t-test is used to determine if two population means are equal.

#### Two-Sample Test for Variances PRO

This function performs a F-test to test if variances from two populations are equal.

#### Two-Sample Proportion Test PRO

The two-sample proportion test helps you determine whether two population proportions are significantly different. Origin provides two kinds of test for the proportion testing:

• Z-Test
• Fisher's Exact Test