Coefficient of multiple correlation: Difference between revisions

Revision as of 16:39, 31 March 2024

Latest revision as of 16:43, 31 March 2024

(One intermediate revision by the same user not shown)

Line 4:

In [[statistics]], the '''coefficient of multiple correlation''' is a measure of how well a given variable can be predicted using a [[linear function]] of a set of other variables. It is the [[Pearson correlation|correlation]] between the variable's values and the best predictions that can be computed [[linear equation|linearly]] from the predictive variables.<ref>[http://onlinestatbook.com/2/regression/multiple_regression.html Introduction to Multiple Regression] </ref>

The absolute valuecoefficient of the multiple correlation takes values between -10 and 1. Higher absolute values indicate higher predictability of the [[dependent and independent variables|dependent variable]] from the [[dependent and independent variables|independent variables]], with a value of 1 indicating that the predictions are exactly correct and a value of 0 indicating that no linear combination of the independent variables is a better predictor than is the fixed [[mean]] of the dependent variable.<ref>[http://mtweb.mtsu.edu/stats/regression/level3/multicorrel/multicorrcoef.htm Multiple correlation coefficient]</ref>

{| class="wikitable"

|Correlation Coefficient (r)