## What is a no Parametric Test?

A non parametric test (sometimes referred to as a distribution free test) does no assume anything around the underlying circulation (for example, the the data comes from a common distribution). That’s compared to parametric test, which provides assumptions about a population’s parameters (for example, the typical or conventional deviation); once the indigenous “non parametric” is offered in stats, it doesn’t quite mean that you know nothing around the population. That usually means that you know the population data does not have a typical distribution.

Watch the video clip to see the differences in between parametric and also non-parametric tests, and also when you might want to usage non-parametric tests:

For example, one assumption for the one method ANOVA is the the data originates from a typical distribution. If her data isn’t normally distributed, girlfriend can’t run an ANOVA, yet you deserve to run the nonparametric alternative—the Kruskal-Wallis test.

If at all possible, you have to us parametric tests, as they tend to be an ext accurate. Parametric exam have better statistical power, which way they are most likely to discover a true far-ranging effect. Usage nonparametric tests only if you need to (i.e. You understand that assumptions like normality space being violated). Nonparametric tests deserve to perform well v non-normal continuous data if you have actually a sufficiently huge sample dimension (generally 15-20 items in every group).

## When to usage it

Non parametric test are offered when your data isn’t normal. Because of this the crucial is to figure out if you have normally dispersed data. For example, you could look in ~ the distribution of her data. If her data is approximately normal, climate you have the right to use parametric statistics tests.

You are watching: Nonparametric procedures are usually not our first choice among statistical procedures because

Q. If friend don’t have a graph, just how do you figure out if your data is typically distributed?A. check the skewness and Kurtosis the the circulation using software choose Excel (See: Skewness in Excel 2013 and Kurtosis in Excel 2013).A normal circulation has no skew. Basically, it’s a centered and also symmetrical in shape. Kurtosis ad to exactly how much that the data is in the tails and the center. The skewness and also kurtosis for a normal distribution is about 1. Negative kurtosis (left) and also positive kurtosis (right)

If your distribution is not normal (in various other words, the skewness and kurtosis deviate a lot native 1.0), you need to use a no parametric test favor chi-square test. Otherwise you operation the risk that your outcomes will be meaningless.

## Data Types

Does your data enable for a parametric test, or do you have to use a no parametric test favor chi-square? The dominion of thumb is: A skewed distribution is one factor to run a nonparametric test.

Other reasons to run nonparametric tests:One or an ext assumptions of a parametric test have been violated.

## Types the Nonparametric Tests

When the word “parametric” is offered in stats, that usually method tests favor ANOVA or a t test. Those exam both assume the the population data has a regular distribution. Non parametric perform not assume that the data is usually distributed. The just non parametric check you are most likely to come throughout in primary school stats is the chi-square test. However, over there are numerous others. For example: the Kruskal Willis test is the no parametric different to the One means ANOVA and also the Mann Whitney is the non parametric different to the 2 sample t test.

The key nonparametric tests are:

The adhering to table lists the nonparametric tests and their parametric alternatives.

Nonparametric testParametric Alternative
1-sample sign testOne-sample Z-test, One sample t-test
1-sample Wilcoxon Signed rank testOne sample Z-test, One sample t-test
Friedman testTwo-way ANOVA
Kruskal-Wallis testOne-way ANOVA
Mann-Whitney testIndependent samples t-test
Mood’s typical testOne-way ANOVA
Spearman rank CorrelationCorrelation Coefficient

Compared to parametric tests, nonparametric tests have several advantages, including:

Small sample sizes room acceptable.

However, they do have their disadvantages. The many notable ones are:

Less powerful than parametric tests if presumptions haven’t been violated.More labor-intensive to calculate by hand (for computer calculations, this isn’t an issue).

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## References

Kotz, S.; et al., eds. (2006), Encyclopedia of statistical Sciences, Wiley.Lindstrom, D. (2010). Schaum’s Easy outline of Statistics, second Edition (Schaum’s easy Outlines) second Edition. McGraw-Hill Education

CITE THIS AS:Stephanie Glen. "Non Parametric Data and also Tests (Distribution free Tests)" native brickandmortarphilly.com: primary school Statistics because that the remainder of us! https://www.brickandmortarphilly.com/probability-and-statistics/statistics-definitions/parametric-and-non-parametric-data/
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