Pearson Correlation Coefficient Origin
The Pearson correlation coefficient, although named after statistician Karl Pearson, has a more interesting backstory. The concept of correlation itself can be traced back to Francis Galton, a 19th-century scientist and explorer. Galton was fascinated by inheritance and explored relationships between traits in families.
While Galton planted the seed for the idea, the mathematical formula behind the coefficient actually came from French physicist Auguste Bravais in 1844. However, it was Karl Pearson who truly championed the concept in the late 1800s. He refined the mathematical treatment, explored its properties, and popularized its use in statistical analysis. For this reason, the coefficient bears his name, even though earlier contributions played a crucial role in its development.
Pearson Correlation Coefficient
Pearson Correlation Coefficient: Correlation coefficients are used to measure how strong a relationship is between two variables. There are different types of formulas to get a correlation coefficient, one of the most popular is Pearson’s correlation (also known as Pearson’s r) which is commonly used for linear regression.
The Pearson correlation coefficient, often symbolized as (r), is a widely used metric for assessing linear relationships between two variables. It yields a value ranging from –1 to 1, indicating both the magnitude and direction of the correlation. A change in one variable is mirrored by a corresponding change in the other variable in the same direction.
This article provides detailed information on the Pearson Correlation Coefficient, its meaning, formula, interpretation, examples, and FAQs.
Table of Content
- What is the Pearson Correlation Coefficient?
- Pearson’s Correlation Coefficient Formula
- Pearson Correlation Coefficient Table
- Pearson Correlation Coefficient Origin
- Types of Pearson Correlation Coefficient
- Adjusted Correlation Coefficient
- Weighted Correlation Coefficient
- Reflective Correlation Coefficient
- Scaled Correlation Coefficient
- Pearson’s Distance
- Circular Correlation Coefficient
- Partial Correlation
- Pearson Correlation Coefficient Interpretation
- Finding the Correlation Coefficient with Pearson Correlation Coefficient Formula
- Assumptions of Pearson Correlation Coefficient
- Correlation Coefficient Properties
- Pearson Correlation Coefficient Interpretation
- Bivariate Correlation
- Correlation Matrix
- Pearson Correlation Coefficient Examples
- Pearson Correlation Coefficient Practice Problems
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