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DATA ANALYSIS USING THE METHOD OF LEAST SQUARES

EXTRACTING THE MOST INFORMATION FROM EXPERIMENTS

WOLBERG J.

SPRINGER,
250 pages, 58 illus., Softcover

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.

Table of contents

Introduction.
The Method of Least Squares.
Model Evaluation.
Candidate Predictors.
Designing Quantitative Experiments.
Software.
Kernel Regression.

250 pages, 58 illus., Softcover

Written for: Engineers, scientists, graduate students in quantitative disciplines

Keywords:Curve Fitting, Data Analysis, Least Squares, Nonlinear Models, Parametric Models