Data Analysis Using the Method of Least Squares: Extracting the Most Information from Experiments
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Overview
Develops the full power of the least-squares method
Enables engineers and scientists to apply the method to their specific problem
Deals with linear as well as with non-linear least-squares, parametric as well as non-parametric methods
Synopsis
The preferred method of data analysis of quantitative experiments is the method of least squares. Often, however, the full power of the method is overlooked and very few books deal with this subject at the level that it deserves. The purpose of Data Analysis Using the Method of Least Squares is to fill this gap and include the type of information required to help scientists and engineers apply the method to problems in their special fields of interest. In addition, graduate students in science and engineering doing work of experimental nature can benefit from this book. Particularly, both linear and non-linear least squares, the use of experimental error estimates for data weighting, procedures to include prior estimates, methodology for selecting and testing models, prediction analysis, and some non-parametric methods are discussed.