multiple correlation coefficient (Meaning)
multiple correlation coefficient (n)
an estimate of the combined influence of two or more variables on the observed (dependent) variable
Synonyms & Antonyms of multiple correlation coefficient
No Synonyms and anytonyms found
multiple correlation coefficient Sentence Examples
- The multiple correlation coefficient (R) measures the linear relationship between a dependent variable and multiple independent variables.
- A higher multiple correlation coefficient indicates a stronger linear relationship between the variables.
- The multiple correlation coefficient ranges from 0 to 1, with 0 indicating no relationship and 1 indicating a perfect relationship.
- The squared multiple correlation coefficient (R-squared) represents the proportion of variance in the dependent variable that is explained by the independent variables.
- The multiple correlation coefficient is affected by the number of independent variables included in the analysis.
- Adding more independent variables to a regression model can increase the multiple correlation coefficient, but it can also lead to overfitting.
- The multiple correlation coefficient can be used to compare the predictive power of different regression models.
- The multiple correlation coefficient is used in various applications, including statistical modeling, machine learning, and data analysis.
- A high multiple correlation coefficient does not necessarily imply causality between the variables.
- The multiple correlation coefficient is a useful tool for assessing the strength and direction of the linear relationship between variables.
FAQs About the word multiple correlation coefficient
an estimate of the combined influence of two or more variables on the observed (dependent) variable
No synonyms found.
No antonyms found.
The multiple correlation coefficient (R) measures the linear relationship between a dependent variable and multiple independent variables.
A higher multiple correlation coefficient indicates a stronger linear relationship between the variables.
The multiple correlation coefficient ranges from 0 to 1, with 0 indicating no relationship and 1 indicating a perfect relationship.
The squared multiple correlation coefficient (R-squared) represents the proportion of variance in the dependent variable that is explained by the independent variables.
