Kendall's W and Pearson correlation coefficient

Shortcuts: Differences, Similarities, Jaccard Similarity Coefficient, References.

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).

Kendall's W and Nonparametric statistics · Nonparametric statistics and Pearson correlation coefficient · See more »

Normal distribution

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

Kendall's W and Normal distribution · Normal distribution and Pearson correlation coefficient · See more »

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.

Kendall's W and Probability distribution · Pearson correlation coefficient and Probability distribution · See more »

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).

Kendall's W and Spearman's rank correlation coefficient · Pearson correlation coefficient and Spearman's rank correlation coefficient · See more »

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.

Kendall's W and Statistical hypothesis testing · Pearson correlation coefficient and Statistical hypothesis testing · See more »

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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