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Residuals

By Jim Frost

In statistical models, a residual is the difference between the observed value and the mean value that the model predicts for that observation. Residual values are especially useful in regression and ANOVA procedures because they indicate the extent to which a model accounts for the variation in the observed data.

Related

Related Articles:
  • How To Interpret R-squared in Regression Analysis
  • Curve Fitting using Linear and Nonlinear Regression
  • How High Does R-squared Need to Be?
  • Using Data Mining to Select Regression Models Can Create Serious Problems
  • Mean Squared Error (MSE)

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