Building upon the fundamental principles of decision theory, Decision-Based Design: Integrating Consumer Preferences into Engineering Design presents an analytical approach to enterprise-driven Decision-Based Design (DBD) as a rigorous framework for decision making in engineering design. Once the related fundamentals of decision theory, economic analysis, and econometrics modelling are established, the remaining chapters describe the entire process, the associated analytical techniques, an...

An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance to marketing to astrophysics in the past twenty years. This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling met...

With emphasis on practical aspects of engineering, this bestseller has gained worldwide recognition through progressive editions as the essential reliability textbook. This fifth edition retains the unique balanced mixture of reliability theory and applications, thoroughly updated with the latest industry best practices.Practical Reliability Engineering fulfils the requirements of the Certified Reliability Engineer curriculum of the American Society for Quality (A...

This second edition has been updated and revised to reflect the most recent Six Sigma techniques, and to match 2007 version of the ASQ Certified Six Sigma Black Belt Body of Knowledge (BOK).While the primary audience for this work is the individual preparing to sit for the Six Sigma Black Belt certification examination, a secondary audience for the handbook is the quality and Six Sigma professional who would like a relevant Six Sigma reference book. With this audience in mind, the authors ...

Data mining is the process of automatically searching large volumes of data for models and patterns using computational techniques from statistics, machine learning and information theory; it is the ideal tool for such an extraction of knowledge. Data mining is usually associated with a business or an organization's need to identify trends and profiles, allowing, for example, retailers to discover patterns on which to base marketing objectives.This book looks at both classical and ...

This book aims to enable readers to understand and implement, via the widely used statistical software package Minitab (Release 16), statistical methods fundamental to the Six Sigma approach to the continuous improvement of products, processes and services.The second edition includes the following new material:Pareto charts and Cause-and-Effect diagramsTime-weighted control charts cumulative sum (CUSUM) and exponentially weighted moving average (EWMA)

An introduction to statistical data mining, Data Analysis and Data Mining is both textbook and professional resource. Assuming only a basic knowledge of statistical reasoning, it presents core concepts in data mining and exploratory statistical models to students and professional statisticians-both those working in communications and those working in a technological or scientific capacity-who have a limited knowledge of data mining. This book presents key statistical concepts by w...

This accessible, practice-oriented and compact text provides a hands-on introduction to the principles of market research. Using the market research process as a framework, the authors explain how to collect and describe the necessary data and present the most important and frequently used quantitative analysis techniques, such as ANOVA, regression analysis, factor analysis, and cluster analysis. An explanation is provided of the theoretical choices a market researcher has to make with reg...

Data Mining Applications with R is a great resource for researchers and professionals to understand the wide use of R, a free software environment for statistical computing and graphics, in solving different problems in industry. R is widely used in leveraging data mining techniques across many different industries, including government, finance, insurance, medicine, scientific research and more. This book presents 15 different real-world case studies illustrating various techniques in rap...

Computational intelligence, a sub-branch of artificial intelligence, is a field which draws on the natural world and adaptive mechanisms in order to study behaviour in changing complex environments. This book provides an interdisciplinary view of current technological advances and challenges concerning the application of computational intelligence techniques to financial time-series forecasting, trading and investment.The book is divided into five parts. The first part introduces t...

Solutions Manual to accompany Statistical Data Analytics: Foundations for Data Mining, Informatics, and Knowledge DiscoveryA comprehensive introduction to statistical methods for data mining and knowledge discovery.Extensive solutions using actual data (with sample R programming code) are provided, illustrating diverse informatic sources in genomics, biomedicine, ecological remote sensing, astronomy, socioeconomics, marketing, advertising and...

Reliability, Maintainability and Risk: Practical Methods for Engineers, Eighth Edition, discusses tools and techniques for reliable and safe engineering, and for optimizing maintenance strategies. It emphasizes the importance of using reliability techniques to identify and eliminate potential failures early in the design cycle. The focus is on techniques known as RAMS (reliability, availability, maintainability, and safety-integrity). The book is organized into five parts. Part 1 on reliab...