Statistics Definitions > Parametric Statistics
What are “Parametric Statistics”?
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.
Every parametric test has a nonparametric equivalent. For example, if you have parametric data from two independent groups, you can run an independent samples t-test to compare means. If you have nonparametric data, you can run a Mann Whitney test instead.
Watch the video to see the differences between parametric and non-parametric tests:
Data that is assumed to have been drawn from a particular distribution, and that is used in a parametric test.
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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Vogt, W.P. (2005). Dictionary of Statistics & Methodology: A Nontechnical Guide for the Social Sciences. SAGE.
Stephanie Glen. "Parametric Statistics, Tests and Data" From StatisticsHowTo.com: Elementary Statistics for the rest of us! https://www.statisticshowto.com/parametric-statistics/
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