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Linear Regression by Least Squares

  • Richard M. Heiberger
  • Burt Holland
Part of the Springer Texts in Statistics book series (STS)

Abstract

We usually study more than one variable at a time. When the variables are continuous, and one is clearly a response variable and the others are predictor variables, we usually plot the variables and then attempt to fit a model to the plotted points. With one continuous predictor, the first model we attempt is a straight line; with two or more continuous predictors, we attempt a plane. We plot the model, the residuals from the model, and various diagnostics of the quality of the fit.

Keywords

Simple Linear Regression Prediction Interval Calculated Residual Residual Standard Error Residual Line 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media New York 2004

Authors and Affiliations

  • Richard M. Heiberger
    • 1
  • Burt Holland
    • 1
  1. 1.Department of StatisticsTemple UniversityPhiladelphiaUSA

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