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Error analysis (Mathematics)

Most popular at the top

  • Data Analysis Using the Method of Least Squaresby John Wolberg

    Springer-Verlag Berlin and Heidelberg GmbH & Co. KG 2006; US$ 99.00

    Discusses 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 Uncertaintiesby Springer

    Springer 2009; US$ 179.00

    Dealing 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...

  • Measurement Errorby John P. Buonaccorsi

    Taylor and Francis 2010; US$ 104.95

    Over the last 20 years, comprehensive strategies for treating measurement error in complex models and accounting for the use of extra data to estimate measurement error parameters have emerged. Focusing on both established and novel approaches, Measurement Error: Models, Methods, and Applications provides an overview of the main techniques and illustrates... more...

  • Generalized Gaussian Error Calculusby Michael Grabe

    Springer 2010; US$ 189.00

    The 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...

  • Error and the Growth of Experimental Knowledgeby Deborah G. Mayo

    University of Chicago Press 1996; US$ 36.00

    We 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...

  • Measures of Interobserver Agreement and Reliabilityby Mohamed M. Shoukri

    Taylor and Francis 2003; US$ 97.95

    Agreement among at least two evaluators is an issue of prime importance to statisticians, clinicians, epidemiologists, psychologists, and many other scientists. Measuring interobserver agreement is a method used to evaluate inconsistencies in findings from different evaluators who collect the same or similar information. Highlighting applications over... more...