statistical measure of goodness-of-fit. It measures how good the estimated regression equation is, designated asr 2(read as r-squared). The higher the r-squared, the more confidence one can have in the equation. Statistically, the coefficient of determination represents the proportion of the total variation in the y variable that is explained by the regression equation. It has the range of values between 0 and 1. It is computed as
see also regression analysis.
Example:The statement "factory overhead is a function of machinehours withr 2= .70," can be interpreted as "70% of the total variation of factory overhead is explained by the machine hours and the remaining 30% is accounted for by something other than machine-hours." The 30% is referred to as the error term.
test statistic that shows the amount of variability in a dependent variable explained by the regression model's independent variable(s). It is denoted by R2 and ranges from 0 to 1. If 0, there is no explanation of the dependent variable at all; if 1, the independent variables explain all the variability of the dependent variable.
statistical measure of relative variation that describes the variation in one value that occurs in proportion to variations in another value. The coefficient of determination is symbolized as R2.
