Praise for the Fourth Edition "As with previous editions, the authors have produced a leading textbook on regression." —Journal of the American Statistical Association A comprehensive and up-to-date introduction to the fundamentals of regression analysis Introduction to Linear Regression Analysis, Fifth Edition continues to present both the conventional and less common uses of linear regression in today’s cutting-edge scientific research. The authors blend both theory and application to equip readers with an understanding of the basic principles needed to apply regression model-building techniques in various fields of study, including engineering, management, and the health sciences. Following a general introduction to regression modeling, including typical applications, a host of technical tools are outlined such as basic inference procedures, introductory aspects of model adequacy checking, and polynomial regression models and their variations. The book then discusses how transformations and weighted least squares can be used to resolve problems of model inadequacy and also how to deal with influential observations. The Fifth Edition features numerous newly added topics, including: A chapter on regression analysis of time series data that presents the Durbin-Watson test and other techniques for detecting autocorrelation as well as parameter estimation in time series regression models Regression models with random effects in addition to a discussion on subsampling and the importance of the mixed model Tests on individual regression coefficients and subsets of coefficients Examples of current uses of simple linear regression models and the use of multiple regression models for understanding patient satisfaction data. In addition to Minitab, SAS, and S-PLUS, the authors have incorporated JMP and the freely available R software to illustrate the discussed techniques and procedures in this new edition. Numerous exercises have been added throughout, allowing readers to test their understanding of the material. Introduction to Linear Regression Analysis, Fifth Edition is an excellent book for statistics and engineering courses on regression at the upper-undergraduate and graduate levels. The book also serves as a valuable, robust resource for professionals in the fields of engineering, life and biological sciences, and the social sciences.

Das bewährte Handbuch zum Statistiktool Six Sigma - jetzt in neuer, aktualisierter Auflage! - besprochen werden täglich benötigte Verfahren und deren Implementation - erweiterte Behandlung u.a. des Benchmarkings - mit vielen praxisnahen Übungen - enthält Pläne, Checklisten und Übersichten häufig auftretender Fehler

Through the use of practical examples and solutions, Pharmaceutical Statistics: Practical and Clinical Applications, Fifth Edition provides the most complete and comprehensive guide to the various statistical applications and research issues in the pharmaceutical industry, particularly in clinical trials and bioequivalence studies.

This book focuses on AI and data-driven technical and management innovations in logistics, informatics and services. The respective papers analyze in detail the latest fundamental advances in the state of the art and practice of logistics, informatics, service operations and service science. The book gathers the outcomes of the “9th International Conference on Logistics, Informatics and Service Sciences,” which was held at the University of Maryland, USA.

Power systems are evolving towards the Smart Grid paradigm, featured by large-scale integration of renewable energy resources, e.g. wind and solar power, deeper participation of demand side, and enhanced interaction with electric vehicles. While these emerging elements are inherently stochastic in nature, they are creating a challenge to the system’s stability and its control. In this context, conventional analysis tools are becoming less effective, and necessitate the use alternative tools that are able to deal with the high uncertainty and variability in the smart grid. Smart Grid initiatives have facilitated wide-spread deployment of advanced sensing and communication infrastructure, e.g. phasor measurement units at grid level and smart meters at household level, which collect tremendous amount of data in various time and space scales. How to fully utilize the data and extract useful knowledge from them, is of great importance and value to support the advanced stability assessment and control of the smart grid. The intelligent system strategy has been identified as an effective approach to meet the above needs. This book presents the cutting-edge intelligent system techniques and their applications for stability assessment and control of power systems. The major topics covered in this book are: Intelligent system design and algorithms for on-line stability assessment, which aims to use steady-state operating variables to achieve fast stability assessment for credible contingencies. Intelligent system design and algorithms for preventive stability control, which aims at transparent and interpretable decision-making on preventive control actions to manipulate system operating condition against possible contingencies. Intelligent system design and algorithms for real-time stability prediction, which aims to use synchronized measurements to foresee the stability status under an ongoing disturbance. Intelligent system design and algorithms for emergency stability control, which aims at fast decision-making on stability control actions at emergency stage where instability is propagating. Methodologies and algorithms for improving the robustness of intelligent systems against missing-data issues. This book is a reference and guide for researchers, students, and engineers who seek to study and design intelligent systems to resolve stability assessment and control problems in the smart grid age.

This user-friendly guide illustrates how to assess measurement invariance using computer programs, statistical methods, and real data.

Value Creation and its effects on Transfer Pricing and tax law Emerging from the OECD/G20 BEPS Project, a new, somewhat fuzzy notion of Value Creation came to permeate not only Transfer Pricing language but also wider allocation rules and anti-abuse provisions in international tax law. The notion of ‘Value Creation’ reframes the interpretation and application of the Arm’s Length Principle (ALP) that is embedded in Articles 7 and 9 of the OECD Model Convention. This new Value Creation notion and approach assist in understanding key enterprise functions while different industry sectors manifest these concepts in various ways. Situating such notions and this approach within the law of tax treaties and analyzing terms of the OECD Transfer Pricing Guidelines alongside their factual context is the aim of this book. Here, law students address Transfer Pricing and Value Creation in sectors as varied as commodities trade, automotive, consumer products, food and beverages, pharmaceutical and life sciences, telecommunications, and the key topic of value creation in a digitalized economy. Our LL.M. students were required to address issues not explored in legal research and to discuss factual topics relevant for Transfer Pricing. All students focused on topics that are new to the international tax debate that keep evolving and on factual matters that often escape legal research.

Business Statistics offers readers a foundation in core statistical concepts using a perfect blend of theory and practical application. This book presents business statistics as value added tools in the process of converting data into useful information. The step-by-step approach used to discuss three main statistical software applications, MS Excel, Minitab, and SPSS, which are critical tools for decision making in the business world, makes this book extremely user friendly. India-centric case studies and examples demonstrate the many uses of statistics in business and economics. The underlying focus on the interpretation of results rather than computation makes this book highly relevant for students and practising managers. Practice quizzes and true/false questions for students, and lecture slides and solutions manual for instructors are available at http://wps.pearsoned.com/bajpai_businessstatistics_e.

This book covers techniques that can be used to analyze data from IoT sensors and addresses questions regarding the performance of an IoT system. It strikes a balance between practice and theory so one can learn how to apply these tools in practice with a good understanding of their inner workings. This is an introductory book for readers who have no familiarity with these techniques. The techniques presented in An Introduction to IoT Analytics come from the areas of machine learning, statistics, and operations research. Machine learning techniques are described that can be used to analyze IoT data generated from sensors for clustering, classification, and regression. The statistical techniques described can be used to carry out regression and forecasting of IoT sensor data and dimensionality reduction of data sets. Operations research is concerned with the performance of an IoT system by constructing a model of the system under study and then carrying out a what-if analysis. The book also describes simulation techniques. Key Features IoT analytics is not just machine learning but also involves other tools, such as forecasting and simulation techniques. Many diagrams and examples are given throughout the book to fully explain the material presented. Each chapter concludes with a project designed to help readers better understand the techniques described. The material in this book has been class tested over several semesters. Practice exercises are included with solutions provided online at www.routledge.com/9780367686314 Harry G. Perros is a Professor of Computer Science at North Carolina State University, an Alumni Distinguished Graduate Professor, and an IEEE Fellow. He has published extensively in the area of performance modeling of computer and communication systems.