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Coefficient of Determination

Coefficient of Determination:

In regression analysis, the coefficient of determination is a measure of goodness-of-fit (i.e. how well or tightly the data fit the estimated model). The coefficient is defined as the ratio of two sums of squares:

 

r2 =  SSR


SST

,

where SSR is the sum of squares due to regression, SST is the total sum of squares. By "sum of squares" we mean the sum of squared deviations between actual values and the mean (SST), or between predicted values and the mean (SSR). The coefficient of determination takes on values between 0 and 1, with values closer to 1 implying a better fit.

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Courses Using This Term

Regression Analysis
This course will teach you how multiple linear regression models are derived, the use software to implement them, what assumptions underlie the models, how to test whether your data meet those assumptions and what can be done when those assumptions are not met, and develop strategies for building and understanding useful models.
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