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The coefficient of multiple correlation takes values between 0 and 1. Higher 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)
|Direction and Strength of Correlation
|-
|1
|Perfectly positive
|-
|0.8
|Strongly positive
|-
|0.5
|Moderately positive
|-
|0.2
|Weakly positive
|-
|0
|No association
|-
| -0.2
|Weakly negative
|-
| -0.5
|Moderately negative
|-
| -0.8
|Strongly negative
|-
| -1
|Perfectly negative
|}
The coefficient of multiple correlation is known as the square root of the [[coefficient of determination]], but under the particular assumptions that an intercept is included and that the best possible linear predictors are used, whereas the coefficient of determination is defined for more general cases, including those of nonlinear prediction and those in which the predicted values have not been derived from a model-fitting procedure.
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