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Statistical Methods in Software Engineering - Reliability and Risk (Hardcover, 1999 ed.): Nozer D Singpurwalla, Simon P. Wilson Statistical Methods in Software Engineering - Reliability and Risk (Hardcover, 1999 ed.)
Nozer D Singpurwalla, Simon P. Wilson
R4,177 Discovery Miles 41 770 Ships in 18 - 22 working days

In establishing a framework for dealing with uncertainties in software engineering, and for using quantitative measures in related decision-making, this text puts into perspective the large body of work having statistical content that is relevant to software engineering. Aimed at computer scientists, software engineers, and reliability analysts who have some exposure to probability and statistics, the content is pitched at a level appropriate for research workers in software reliability, and for graduate level courses in applied statistics computer science, operations research, and software engineering.

Analytical and Computational Methods in Probability Theory - First International Conference, ACMPT 2017, Moscow, Russia,... Analytical and Computational Methods in Probability Theory - First International Conference, ACMPT 2017, Moscow, Russia, October 23-27, 2017, Proceedings (Paperback, 1st ed. 2017)
Vladimir V. Rykov, Nozer D Singpurwalla, Andrey M. Zubkov
R1,479 Discovery Miles 14 790 Ships in 18 - 22 working days

This book constitutes the refereed proceedings of the First International Conference on Analytical and Computational Methods in Probability Theory and its Applications, ACMPT 2017, held in Moscow, Russia, in October 2017. The 42 full papers presented were carefully reviewed and selected from 173 submissions. The conference program consisted of four main themes associated with significant contributions made by A.D.Soloviev. These are: Analytical methods in probability theory, Computational methods in probability theory, Asymptotical methods in probability theory, the history of mathematics.

Statistical Methods in Software Engineering - Reliability and Risk (Paperback, Softcover reprint of the original 1st ed. 1999):... Statistical Methods in Software Engineering - Reliability and Risk (Paperback, Softcover reprint of the original 1st ed. 1999)
Nozer D Singpurwalla, Simon P. Wilson
R2,885 Discovery Miles 28 850 Ships in 18 - 22 working days

In establishing a framework for dealing with uncertainties in software engineering, and for using quantitative measures in related decision-making, this text puts into perspective the large body of work having statistical content that is relevant to software engineering. Aimed at computer scientists, software engineers, and reliability analysts who have some exposure to probability and statistics, the content is pitched at a level appropriate for research workers in software reliability, and for graduate level courses in applied statistics computer science, operations research, and software engineering.

Case Studies in Bayesian Statistics - Volume III (Paperback, Softcover reprint of the original 1st ed. 1997): Constantine... Case Studies in Bayesian Statistics - Volume III (Paperback, Softcover reprint of the original 1st ed. 1997)
Constantine Gatsonis, James S Hodges, Robert E. Kass, Robert E. Mcculloch, Peter Rossi, …
R2,707 Discovery Miles 27 070 Ships in 18 - 22 working days

This third volume of case studies presents detailed applications of Bayesian statistical analysis, emphasising the scientific context. The papers were presented and discussed at a workshop held at Carnegie-Mellon University, and this volume - dedicated to the memory of Morrie Groot-reproduces six invited papers, each with accompanying invited discussion, and nine contributed papers with the focus on econometric applications.

Case Studies in Bayesian Statistics, Volume II (Paperback, Softcover reprint of the original 1st ed. 1995): Constantine... Case Studies in Bayesian Statistics, Volume II (Paperback, Softcover reprint of the original 1st ed. 1995)
Constantine Gatsonis, James S Hodges, Robert E. Kaas, Nozer D Singpurwalla
R2,676 Discovery Miles 26 760 Ships in 18 - 22 working days

Like its predecessor, this second volume presents detailed applications of Bayesian statistical analysis, each of which emphasizes the scientific context of the problems it attempts to solve. The emphasis of this volume is on biomedical applications. These papers were presented at a workshop at Carnegie-Mellon University in 1993.

Case Studies in Bayesian Statistics (Paperback, Softcover reprint of the original 1st ed. 1993): Constantine Gatsonis, James S... Case Studies in Bayesian Statistics (Paperback, Softcover reprint of the original 1st ed. 1993)
Constantine Gatsonis, James S Hodges, Robert E. Kass, Nozer D Singpurwalla
R2,695 Discovery Miles 26 950 Ships in 18 - 22 working days

The past few years have witnessed dramatic advances in computational methods for Bayesian inference. As a result, Bayesian approaches to solving a wide variety of problems in data analysis and decision-making have become feasible, and there is currently a growth spurt in the application of Bayesian methods. The purpose of this volume is to present several detailed examples of applications of Bayesian thinking, with an emphasis on the scientific or technological context of the problem being solved. The papers collected here were presented and discussed at a Workshop held at Carnegie-Mellon University, September 29 through October 1, 1991. There are five ma jor articles, each with two discussion pieces and a reply. These articles were invited by us following a public solicitation of abstracts. The problems they address are diverse, but all bear on policy decision-making. Though not part of our original design for the Workshop, that commonality of theme does emphasize the usefulness of Bayesian meth ods in this arena. Along with the invited papers were several additional commentaries of a general nature; the first comment was invited and the remainder grew out of the discussion at the Workshop. In addition there are nine contributed papers, selected from the thirty-four presented at the Workshop, on a variety of applications. This collection of case studies illustrates the ways in which Bayesian methods are being incorporated into statistical practice. The strengths (and limitations) of the approach become apparent through the examples."

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