Pearson Correlation Coefficient Table
Pearson Correlation Coefficient (r) Range | Type of Correlation | Description of Relationship | New Illustrative Example |
---|---|---|---|
0 < r ≤ 1 | Positive | An increase in one variable associates with an increase in the other. | Study Time vs. Test Scores: More hours spent studying tends to lead to higher test scores. |
r = 0 | None | No discernible relationship between the changes in both variables. | Shoe Size vs. Reading Skill: A person’s shoe size doesn’t predict their ability to read. |
-1 ≤ r < 0 | Negative | An increase in one variable associates with a decrease in the other. | Outdoor Temperature vs. Home Heating Cost: As the outdoor temperature decreases, heating costs in the home increase. |
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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