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Coefficient of Determination

Reviewed by Sweta | Updated on Oct 05, 2020



Coefficient of determination refers to a statistical measure to derive, analyse, and understand the behaviour of variables in a data set. The coefficient examines differences and inter-relation between one variable to the other while determining the result of an event. The coefficient is also known as R-squared or R2 determines the linear relationship between two variables.

Understanding Coefficient of Determination

The coefficient of determination analyses data to examine and explain the relationship between variables and how much the variability of one influences the other. The coefficient is a measure of the goodness of fit. It is one of the complex models of data analysis in statistics which explains the relation between variables.

The coefficient of determination is also known as R2 often lies between 0.0 and 1.0. In case the value of the coefficient is zero, the model is a failure, and the data variables do not fit with each other. In case the value is 1, it indicates that the model is a perfect fit, and both variables are in sync with each other.

In case the value of the coefficient lies between 0 and 1, then the value indicates the relationship between the dependent variable and the independent variable. If the value of the coefficient is 0.3, then 30% of the value of the dependent variable is based on the independent variable.

Plotting of the coefficient of determination on a graph indicates the distance between a fitted line and the various data points which appear on the diagram. The graph also measures the regression line and the closeness between the regression line and the data points. The regression line, which is close to the data points, will have a high level of data fit.


Researchers often use the coefficient of determination for examining and understanding data sets. The coefficient of determination has application in different fields. For example, the coefficient enables determination of the likely date of delivery of baby in the case of pregnancy. The statistical measure thus helps in finding out the correlation between two events, such as the conception and delivery of the baby.

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