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# Kendall's W and Pearson correlation coefficient

## Difference between Kendall's W and Pearson correlation coefficient

### Kendall's W vs. Pearson correlation coefficient

Kendall's W (also known as Kendall's coefficient of concordance) is a non-parametric statistic. In statistics, the Pearson correlation coefficient (PCC, pronounced), also referred to as Pearson's r, the Pearson product-moment correlation coefficient (PPMCC) or the bivariate correlation, is a measure of the linear correlation between two variables X and Y. It has a value between +1 and −1, where 1 is total positive linear correlation, 0 is no linear correlation, and −1 is total negative linear correlation.

## Similarities between Kendall's W and Pearson correlation coefficient

Kendall's W and Pearson correlation coefficient have 5 things in common (in Unionpedia): Nonparametric statistics, Normal distribution, Probability distribution, Spearman's rank correlation coefficient, Statistical hypothesis testing.

### Nonparametric statistics

Nonparametric statistics is the branch of statistics that is not based solely on parameterized families of probability distributions (common examples of parameters are the mean and variance).

### Normal distribution

In probability theory, the normal (or Gaussian or Gauss or Laplace–Gauss) distribution is a very common continuous probability distribution.

### Probability distribution

In probability theory and statistics, a probability distribution is a mathematical function that provides the probabilities of occurrence of different possible outcomes in an experiment.

### Spearman's rank correlation coefficient

In statistics, Spearman's rank correlation coefficient or Spearman's rho, named after Charles Spearman and often denoted by the Greek letter \rho (rho) or as r_s, is a nonparametric measure of rank correlation (statistical dependence between the rankings of two variables).

### Statistical hypothesis testing

A statistical hypothesis, sometimes called confirmatory data analysis, is a hypothesis that is testable on the basis of observing a process that is modeled via a set of random variables.

### The list above answers the following questions

• What Kendall's W and Pearson correlation coefficient have in common
• What are the similarities between Kendall's W and Pearson correlation coefficient

## Kendall's W and Pearson correlation coefficient Comparison

Kendall's W has 12 relations, while Pearson correlation coefficient has 81. As they have in common 5, the Jaccard index is 5.38% = 5 / (12 + 81).

## References

This article shows the relationship between Kendall's W and Pearson correlation coefficient. To access each article from which the information was extracted, please visit:

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