Definitions for **"Coefficient of determination"**

a measure of the proportion of each other's variability that two variables share.

The percentage of variation accounted for in one variable by knowing the value of another variable.

The coefficient of determination is computed by squaring the correlation coefficient It provides an estimate of the proportion of variance in one variable that is predictable front the other variable.

R-squared. The proportion of the variation in the data explained by the model.

A measure of the percent of variation in the dependent variable associated with variation in the value of the interdependent variable. In regression analysis, designated by the term r-square (r2).

A measure used in Regression Analysis, r2 ranges from zero to one and is developed by dividing the variation in Y explained by the regression equation by the total variation in Y, e.g., r2 .89 means 89% of the total variation was explained by the regression equation. www.sceaonline.net Keyword(s): Coefficient of Determination

A measure of the goodness of fit of the relationship between the dependent and independent variables in a regression analysis; for instance, the percentage of variation in the return of an asset explained by the market portfolio return. Also known as R-square.

a correlation of determination, which ranges from 1 to â€“ 1, measures the goodness of fit of a regression line. The correlation coefficient is often used to determine if a manager is properly tracking a specific benchmark/index by examining the relationship between the performance of the fund to the benchmark index. Positive indicates the variables move in the same direction; negative means they are opposite to each other.

Tells us how much variation in the data can be explained by the regression model we have built.

The coefficient of determination, which ranges between 0 and 1, indicates the goodness of fit of a regression model. It shows the proportion of the total variance of the dependent variable explained by the regression model. An R2 of 1 indicates that the model explains all of the variation of the dependent variable. An R2 of 0 indicates that the model explains none of the dependent variable's variance. In many applications, a higher R2 is preferred to a lower one. total variation - unexplained variation= total variation

The square of the correlation coefficient. It is interpreted as the amount of variance in one variable that is accounted for by knowing the second variable.

Displays how strong a correlation may be between two variables

Statistic that measures the proportion of the variation in the dependent variable that is associated with the statistical regression of an independent variable. Can be calculated by taking the square if the correlation coefficient.

The percent of the variability in the dependent variable explained by the independent variable.

In regression analysis this is a statistic (designated as r-squared) indicating the percentage of the change occurring in the dependent variable that is explained by the change in the independent variable(s). The percent change does not necessarily mean there is a cause-and-effect relationship. To Top

In statistics, the coefficient of determination R2 is the proportion of variability in a data set that is accounted for by a statistical model. In this definition, the term "variability" stands for variance or, equivalently, sum of squares. There are several common and equivalent expressions for R2.