Statistical Models In Engineering PDF Download
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Author | : Gerald J. Hahn |
Publisher | : John Wiley & Sons |
Total Pages | : 384 |
Release | : 1967 |
Genre | : Mathematics |
ISBN | : |
Download Statistical Models in Engineering Book in PDF, ePub and Kindle
A detailed treatment on the use of statistical models representing physical phenomena. Considers the relevance of the popular normal distribution models and the applicability of exponential distribution in reliability problems. Introduces and discusses the use of alternate models such as gamma, beta and Weibull distributions. Features expansive coverage of system performance and describes an exact method known as the transformation of variables. Deals with techniques on assessing the adequacy of a chosen model including both graphical and analytical procedures. Contains scores of illustrative examples, most of which have been adapted from actual problems.
Author | : Hahn GJ. |
Publisher | : |
Total Pages | : |
Release | : 1967 |
Genre | : |
ISBN | : |
Download Statistical Models in Engineering Book in PDF, ePub and Kindle
Author | : Jhareswar Maiti |
Publisher | : CRC Press |
Total Pages | : 421 |
Release | : 2022-10-25 |
Genre | : Business & Economics |
ISBN | : 1000618420 |
Download Multivariate Statistical Modeling in Engineering and Management Book in PDF, ePub and Kindle
The book focuses on problem solving for practitioners and model building for academicians under multivariate situations. This book helps readers in understanding the issues, such as knowing variability, extracting patterns, building relationships, and making objective decisions. A large number of multivariate statistical models are covered in the book. The readers will learn how a practical problem can be converted to a statistical problem and how the statistical solution can be interpreted as a practical solution. Key features: Links data generation process with statistical distributions in multivariate domain Provides step by step procedure for estimating parameters of developed models Provides blueprint for data driven decision making Includes practical examples and case studies relevant for intended audiences The book will help everyone involved in data driven problem solving, modeling and decision making.
Author | : V.V. Rykov |
Publisher | : Springer Science & Business Media |
Total Pages | : 465 |
Release | : 2010-11-02 |
Genre | : Technology & Engineering |
ISBN | : 0817649719 |
Download Mathematical and Statistical Models and Methods in Reliability Book in PDF, ePub and Kindle
The book is a selection of invited chapters, all of which deal with various aspects of mathematical and statistical models and methods in reliability. Written by renowned experts in the field of reliability, the contributions cover a wide range of applications, reflecting recent developments in areas such as survival analysis, aging, lifetime data analysis, artificial intelligence, medicine, carcinogenesis studies, nuclear power, financial modeling, aircraft engineering, quality control, and transportation. Mathematical and Statistical Models and Methods in Reliability is an excellent reference text for researchers and practitioners in applied probability and statistics, industrial statistics, engineering, medicine, finance, transportation, the oil and gas industry, and artificial intelligence.
Author | : Hoang Pham |
Publisher | : Springer Nature |
Total Pages | : 497 |
Release | : 2021-08-13 |
Genre | : Technology & Engineering |
ISBN | : 3030769046 |
Download Statistical Reliability Engineering Book in PDF, ePub and Kindle
This book presents the state-of-the-art methodology and detailed analytical models and methods used to assess the reliability of complex systems and related applications in statistical reliability engineering. It is a textbook based mainly on the author’s recent research and publications as well as experience of over 30 years in this field. The book covers a wide range of methods and models in reliability, and their applications, including: statistical methods and model selection for machine learning; models for maintenance and software reliability; statistical reliability estimation of complex systems; and statistical reliability analysis of k out of n systems, standby systems and repairable systems. Offering numerous examples and solved problems within each chapter, this comprehensive text provides an introduction to reliability engineering graduate students, a reference for data scientists and reliability engineers, and a thorough guide for researchers and instructors in the field.
Author | : Nozer D. Singpurwalla |
Publisher | : Springer Science & Business Media |
Total Pages | : 316 |
Release | : 1999-08-05 |
Genre | : Computers |
ISBN | : 0387988238 |
Download Statistical Methods in Software Engineering Book in PDF, ePub and Kindle
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.
Author | : Jorma Rissanen |
Publisher | : Springer Science & Business Media |
Total Pages | : 145 |
Release | : 2007-12-15 |
Genre | : Mathematics |
ISBN | : 0387688129 |
Download Information and Complexity in Statistical Modeling Book in PDF, ePub and Kindle
No statistical model is "true" or "false," "right" or "wrong"; the models just have varying performance, which can be assessed. The main theme in this book is to teach modeling based on the principle that the objective is to extract the information from data that can be learned with suggested classes of probability models. The intuitive and fundamental concepts of complexity, learnable information, and noise are formalized, which provides a firm information theoretic foundation for statistical modeling. Although the prerequisites include only basic probability calculus and statistics, a moderate level of mathematical proficiency would be beneficial.
Author | : Tze Leung Lai |
Publisher | : Springer Science & Business Media |
Total Pages | : 363 |
Release | : 2008-09-08 |
Genre | : Business & Economics |
ISBN | : 0387778276 |
Download Statistical Models and Methods for Financial Markets Book in PDF, ePub and Kindle
The idea of writing this bookarosein 2000when the ?rst author wasassigned to teach the required course STATS 240 (Statistical Methods in Finance) in the new M. S. program in ?nancial mathematics at Stanford, which is an interdisciplinary program that aims to provide a master’s-level education in applied mathematics, statistics, computing, ?nance, and economics. Students in the programhad di?erent backgroundsin statistics. Some had only taken a basic course in statistical inference, while others had taken a broad spectrum of M. S. - and Ph. D. -level statistics courses. On the other hand, all of them had already taken required core courses in investment theory and derivative pricing, and STATS 240 was supposed to link the theory and pricing formulas to real-world data and pricing or investment strategies. Besides students in theprogram,thecoursealso attractedmanystudentsfromother departments in the university, further increasing the heterogeneity of students, as many of them had a strong background in mathematical and statistical modeling from the mathematical, physical, and engineering sciences but no previous experience in ?nance. To address the diversity in background but common strong interest in the subject and in a potential career as a “quant” in the ?nancialindustry,thecoursematerialwascarefullychosennotonlytopresent basic statistical methods of importance to quantitative ?nance but also to summarize domain knowledge in ?nance and show how it can be combined with statistical modeling in ?nancial analysis and decision making. The course material evolved over the years, especially after the second author helped as the head TA during the years 2004 and 2005.
Author | : Bruno Remillard |
Publisher | : CRC Press |
Total Pages | : 490 |
Release | : 2016-04-19 |
Genre | : Business & Economics |
ISBN | : 1439856958 |
Download Statistical Methods for Financial Engineering Book in PDF, ePub and Kindle
While many financial engineering books are available, the statistical aspects behind the implementation of stochastic models used in the field are often overlooked or restricted to a few well-known cases. Statistical Methods for Financial Engineering guides current and future practitioners on implementing the most useful stochastic models used in f
Author | : Hoang Pham |
Publisher | : Springer Nature |
Total Pages | : 1136 |
Release | : 2023-04-20 |
Genre | : Technology & Engineering |
ISBN | : 1447175034 |
Download Springer Handbook of Engineering Statistics Book in PDF, ePub and Kindle
In today’s global and highly competitive environment, continuous improvement in the processes and products of any field of engineering is essential for survival. This book gathers together the full range of statistical techniques required by engineers from all fields. It will assist them to gain sensible statistical feedback on how their processes or products are functioning and to give them realistic predictions of how these could be improved. The handbook will be essential reading for all engineers and engineering-connected managers who are serious about keeping their methods and products at the cutting edge of quality and competitiveness.