Although we classify the fitting procedure into different categories (such as linear fitting, nonlinear fitting), methods of interpreting the regression results are similar. For example, we can tell how good the fit is from R-square, reduced Chi-square value, diagnose the fitting result by residual analysis, etc. We will briefly explain how to interpret the regression result below.
Topics covered in this section:
Bruce Bowerman, Richard T. O'Connell. 1997. Applied Statistics: Improving Business Processes. The McGraw-Hill Companies, Inc.
Sanford Weisberg. 2005. Applied Linear Regression. Third Edition. John Wiley & Son, Inc., Hoboken, New Jersey.
William H. Press et al. 2002. Numerical Recipes in C++, 2nd ed. Cambridge University Press: New York.
Marko Ledvij. Curve Fitting Made Easy. The Industrial Physicist. Apr./May 2003. 9:24-27.