Difference Between Parametric And Nonparametric

Parametric is a statistical test which assumes parameters and the distributions about the population is known. It uses a mean value to measure the central tendency. These tests are common, and therefore the process of performing research is simple. Nonparametric does not make any assumptions and measures the central tendency with median value. Some examples of Nonparametric tests are Kruskal-Wallis, Mann-Whitney, etc.

Difference Between Parametric And Nonparametric

Properties Parametric Nonparametric
Assumptions Yes No
Value for central tendency Mean value Median value
Correlation Pearson Spearman
Probabilistic distribution Normal Arbitrary
Population knowledge Requires Does not require
Used for Interval data Nominal data
Applicability Variables Attributes & Variables
Examples t-test, z-test, etc. Kruskal-Wallis, Mann-Whitney

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