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This book examines important types of control charts for use by engineering students and practitioners. This book contains eight chapters, with Chapter 1 beginning with an introduction, history, and background of control charts. Next. Chapter 2 presents three widely used and some newly developed attributes of control charts. The chapter concludes with some guidelines for implementing control charts. In Chapter 3, the authors present the techniques used effectively in manufacturing units for monitoring the process based upon the inspection of items relating to the variable nature. Chapter 4 discusses attribute and variable control charts using the multiple dependent state sampling. The authors also discuss control chart using process capability index for the normal distribution and non-normal distribution using the multiple dependent state sampling. Chapter 5 presents the concept and
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
An Introduction to Statistical Mechanics and Thermodynamics returns with a second edition which includes new chapters, further explorations, and updated information into the study of statistical mechanics and thermal dynamics. The first part of the book derives the entropy of the classical ideal
Introduction.- Practical Introduction to Business Process Engineering.- Concepts and Modeling Languages.- The Horus Method.- Areas of Application.- The Future of Business Engineering.-
Presenting a fresh look at process control, this new text demonstrates state-space approach shown in parallel with the traditional approach to explain the strategies used in industry today. Modern time-domain and traditional transform-domain methods are integrated throughout and explain the
A comprehensive and self-contained introduction to Gaussian processes, which provide a principled, practical, probabilistic approach to learning in kernel machines.Gaussian processes (GPs) provide a principled, practical, probabilistic approach to learning in kernel machines. GPs have received
A clear and thorough introduction to meta-analysis, the process of synthesizing data from a series of separate studies. The first edition of this text was widely acclaimed for the clarity of the presentation, and quickly established itself as the definitive text in this field. The fully updated
A comprehensive introduction for undergraduate students. Principals of Sensorimotor Control and Learning presents an integrated picture of sensorimotor behaviour. It provides integrated coverage of: brain and behaviour, perception and action, theory and experiment, performance (kinematics and
An introduction to the Bayesian approach to statistical inference that demonstrates its superiority to orthodox frequentist statistical analysis.This book offers an introduction to the Bayesian approach to statistical inference, with a focus on nonparametric and distribution-free methods. It covers
An introduction to the modeling of business information systems, with processes formally modeled using Petri nets.This comprehensive introduction to modeling business-information systems focuses on business processes. It describes and demonstrates the formal modeling of processes in terms of Petri
A valuable new edition of a standard reference The use of statistical methods for categorical data has increased dramatically, particularly for applications in the biomedical and social sciences. An Introduction to Categorical Data Analysis, Third Edition summarizes these methods and shows readers
Introduction.- Geodetic Data Collection Techniques.- Geodetic datum and Geodetic Control Network.- Geoid and Height System.- Reference Ellipsoid and Geodetic Coordinate System.- Gauss and UTM Conformal Projection and Plane Rectangular Coordinate System.- Establishment of Geodetic Coordinate
Preface Chapter 1 Process Simulation in Chemical Engineering 1.1. Introduction 1.2. Chemical process simulators 1.3. Types of process simulators 1.3.1. Simultaneous or Equation oriented simulators 1.3.2. Hybrid simulators 1.3.3. Aspen Plus(R) and Aspen Hysys(R) 1.4. Applications of process
Ecological Models and Data in R is the first truly practical introduction to modern statistical methods for ecology. In step-by-step detail, the book teaches ecology graduate students and researchers everything they need to know in order to use maximum likelihood, information-theoretic, and
This textbook presents a concise yet detailed introduction to quantum physics. Concise, because it condenses the essentials to a few principles. Detailed, because these few principles - necessarily rather abstract - are illustrated by several telling examples. A fairly complete overview of the
Carl Littles introduction offers biographical background and explores Bissells process, motivations, and revelations, and the artist has supplied brief stories for many of the paintings. The path of human experience is joyfully recounted in Hero, illuminated by Bissells animals, who invite our
The definitive guide to the full qualitative research process, from design to dissemination, this is everything you need to understand how good quality research is produced, and how to find, use and enrich your own work with it. New to this edition: - A new structure follows the research process
Offering a solid introduction to the entire modeling process, A FIRST COURSE IN MATHEMATICAL MODELING, 5th Edition delivers an excellent balance of theory and practice, and gives you relevant, hands-on experience developing and sharpening your modeling skills. Throughout, the book emphasizes key
This book aims to cover a broad range of topics in statistical physics, including statistical mechanics (equilibrium and non-equilibrium), soft matter and fluid physics, for applications to biological phenomena at both cellular and macromolecular levels. It is intended to be a graduate level
This textbook offers a concise yet rigorous introduction to calculus of variations and optimal control theory, and is a self-contained resource for graduate students in engineering, applied mathematics, and related subjects. Designed specifically for a one-semester course, the book begins with
This book provides a sound introduction to the use of statistical methods in analytical chemistry, without requiring a strong mathematical
This book provides an introduction to the statistical software R and its application with an empirical approach in finance and economics. It is specifically targeted towards undergraduate and graduate students. It provides beginner-level introduction to R using RStudio and reproducible research