What are the parametric and nonparametric tests for hypothesis testing?

What are the parametric and nonparametric tests for hypothesis testing?

Parametric tests are those that make assumptions about the parameters of the population distribution from which the sample is drawn. This is often the assumption that the population data are normally distributed. Non-parametric tests are “distribution-free” and, as such, can be used for non-Normal variables.

How is Kruskal Wallis calculated?

The Chi-square statistic is an approximation for the exact calculation. Right-tailed the Kruskal Wallis test can use only the right tail….Kruskal Wallis Test.

H=	H’
1 – correction

What is parametric and non parametric test example?

Nonparametric tests are like a parallel universe to parametric tests….Hypothesis Tests of the Mean and Median.

Parametric tests (means)	Nonparametric tests (medians)
2-sample t test	Mann-Whitney test
One-Way ANOVA	Kruskal-Wallis, Mood’s median test
Factorial DOE with one factor and one blocking variable	Friedman test

How do you know which non parametric test to use?

When to use it Non parametric tests are used when your data isn’t normal. Therefore the key is to figure out if you have normally distributed data. For example, you could look at the distribution of your data. If your data is approximately normal, then you can use parametric statistical tests.

What is Z value in Kruskal-Wallis test?

The higher the absolute value, the further a group’s average rank is from the overall average rank. A negative z-value indicates that a group’s average rank is less than the overall average rank. A positive z-value indicates that a group’s average rank is greater than the overall average rank.

Is ANOVA a parametric test?

ANOVA. 1. Also called as Analysis of variance, it is a parametric test of hypothesis testing.