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Parametric Statistics, Tests and Data

Statistics Definitions > Parametric Statistics

What are “Parametric Statistics”?

Parametric can refer to (click to skip to the section):
Parametric Statistical Tests
Parametric Data
Parametric Equations

Parametric Statistical Tests

parametric statistics

The t test in SPSS.




A parameter in statistics refers to an aspect of a population, as opposed to a statistic, which refers to an aspect about a sample. For example, the population mean is a parameter, while the sample mean is a statistic. A parametric statistical test makes an assumption about the population parameters and the distributions that the data came from. These types of test includes Student’s T tests and ANOVA tests, which assume data is from a normal distribution.

The opposite is a nonparametric test, which doesn’t assume anything about the population parameters. Nonparametric tests include chi-square, Fisher’s exact test and the Mann-Whitney test.

Every parametric test has a nonparametric equivalent. For example, if you have parametric data from two independent groups, you can run a 2 sample t test to compare means. If you have nonparametric data, you can run a Wilcoxon rank-sum test to compare means.

Parametric Data Definition

Data that is assumed to have been drawn from a particular distribution, and that is used in a parametric test.

Parametric Equations

Parametric equations are used in calculus to deal with the problems that arise when trying to find functions that describe curves. These equations are beyond the scope of this site, but you can find an excellent rundown of how to use these types of equations here.

Next article: Parametric (When to use a Parametric Test).

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Parametric Statistics, Tests and Data was last modified: October 26th, 2017 by Stephanie Glen