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#### Data Analysis Using the Method of Least Squares

Springer-Verlag Berlin and Heidelberg GmbH & Co. KG 2006; US$ 99.00Discusses 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. This book is useful for scientists, engineers, and students in science and engineering. more...

#### Dealing with Data

Elsevier Science 2013; US$ 72.95Dealing with Data is an introductory course to problems and techniques dealing with data analysis, with emphasis on the physical and engineering sciences. The book starts with the basics of data analysis through non-statistical and non-mathematical assessments of error and uncertainty conditions. Experimental and maximum errors and the use of simple... more...

#### Dealing with Uncertainties

Springer 2007; US$ 89.95Showing that uncertainties are the consequence of modern science rather than of measurements and stressing the importance of the deductive approach to uncertainties, this monograph proposes and explains a fresh approach for the analysis of uncertainties. It also discusses the weakness of using statistical weights in regression analysis. more...

#### Dealing with Uncertainties

Springer 2009; US$ 179.00Dealing with Uncertainties is an innovative monograph that lays special emphasis on the deductive approach to uncertainties and on the shape of uncertainty distributions. This perspective has the potential for dealing with the uncertainty of a single data point and with sets of data that have different weights. It is shown that the inductive approach... more...

#### Error Calculus for Finance and Physics

De Gruyter 2003; US$ 147.00The book deals with propagation of errors on data through mathematical models with applications in finance and physics. It is interesting for scientists and practitioners when studying the sensitivity of their models to small changes in the hypotheses. The book differs from what is usually done in sensitivity analysis because it yields... more...

#### Error and the Growth of Experimental Knowledge

University of Chicago Press 1996; US$ 36.00We may learn from our mistakes, but Deborah Mayo argues that, where experimental knowledge is concerned, we haven't begun to learn enough. Error and the Growth of Experimental Knowledge launches a vigorous critique of the subjective Bayesian view of statistical inference, and proposes Mayo's own error-statistical approach as a more robust framework... more...

#### Generalized Gaussian Error Calculus

Springer 2010; US$ 189.00The proposed book Generalized Gaussian Error Calculus addresses for the first time since 200 years a rigorous, complete and self-consistent revision of the Gaussian error calculus. Since experimentalists realized that measurements in general are burdened by unknown systematic errors, the classical, widespread used evaluation procedures scrutinizing... more...

#### Generalized Least Squares

Wiley 2004; US$ 187.00Generalised Least Squares adopts a concise and mathematically rigorous approach. It will provide an up-to-date self-contained introduction to the unified theory of generalized least squares estimations, adopting a concise and mathematically rigorous approach. The book covers in depth the 'lower and upper bounds approach', pioneered by the first... more...

#### Handbook of Partial Least Squares

Springer 2010; US$ 479.00This handbook provides a comprehensive overview of Partial Least Squares (PLS) methods with specific reference to their use in marketing and with a discussion of the directions of current research and perspectives. It covers the broad area of PLS methods, from regression to structural equation modeling applications, software and interpretation of results.... more...

#### Measurement Error

CRC Press 2010; US$ 109.95Introduction What is measurement error? Some examples The main ingredients Some terminology A look ahead Misclassification in Estimating a Proportion Motivating examples A model for the true values Misclassification models and naive analyses Correcting for misclassification Finite populations Multiple measures with no direct validation... more...