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David Johnson L. Statistical Tools for the Comprehensive Practice of Industrial Hygiene and Environmental Health Sciences


Reviews and reinforces concepts and techniques typical of a first statistics course with additional techniques useful to the IH/EHS practitioner. Includes both parametric and non-parametric techniques described and illustrated in a worker health and environmental protection practice context Illustrated through numerous examples presented in the context of IH/EHS field practice and research, using the statistical analysis tools available in Excel® wherever possible Emphasizes the application of statistical tools to IH/EHS-type data in order to answer IH/EHS-relevant questions Includes an instructor’s manual that follows in parallel with the textbook, including PowerPoints to help prepare lectures and answers in the text as for the Exercises section of each chapter.

8186.15 РУБ

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Pere Cintas Grima Industrial Statistics with Minitab


Industrial Statistics with MINITAB demonstrates the use of MINITAB as a tool for performing statistical analysis in an industrial context. This book covers introductory industrial statistics, exploring the most commonly used techniques alongside those that serve to give an overview of more complex issues. A plethora of examples in MINITAB are featured along with case studies for each of the statistical techniques presented. Industrial Statistics with MINITAB: Provides comprehensive coverage of user-friendly practical guidance to the essential statistical methods applied in industry. Explores statistical techniques and how they can be used effectively with the help of MINITAB 16. Contains extensive illustrative examples and case studies throughout and assumes no previous statistical knowledge. Emphasises data graphics and visualization, and the most used industrial statistical tools, such as Statistical Process Control and Design of Experiments. Is supported by an accompanying website featuring case studies and the corresponding datasets. Six Sigma Green Belts and Black Belts will find explanations and examples of the most relevant techniques in DMAIC projects. The book can also be used as quick reference enabling the reader to be confident enough to explore other MINITAB capabilities.

7367.82 РУБ

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Hengqing Tong Developing Econometrics


Statistical Theories and Methods with Applications to Economics and Business highlights recent advances in statistical theory and methods that benefit econometric practice. It deals with exploratory data analysis, a prerequisite to statistical modelling and part of data mining. It provides recently developed computational tools useful for data mining, analysing the reasons to do data mining and the best techniques to use in a given situation. Provides a detailed description of computer algorithms. Provides recently developed computational tools useful for data mining Highlights recent advances in statistical theory and methods that benefit econometric practice. Features examples with real life data. Accompanying software featuring DASC (Data Analysis and Statistical Computing). Essential reading for practitioners in any area of econometrics; business analysts involved in economics and management; and Graduate students and researchers in economics and statistics.

9451.43 РУБ

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Rassoul Noorossana Statistical Analysis of Profile Monitoring


A one-of-a-kind presentation of the major achievements in statistical profile monitoring methods Statistical profile monitoring is an area of statistical quality control that is growing in significance for researchers and practitioners, specifically because of its range of applicability across various service and manufacturing settings. Comprised of contributions from renowned academicians and practitioners in the field, Statistical Analysis of Profile Monitoring presents the latest state-of-the-art research on the use of control charts to monitor process and product quality profiles. The book presents comprehensive coverage of profile monitoring definitions, techniques, models, and application examples, particularly in various areas of engineering and statistics. The book begins with an introduction to the concept of profile monitoring and its applications in practice. Subsequent chapters explore the fundamental concepts, methods, and issues related to statistical profile monitoring, with topics of coverage including: Simple and multiple linear profiles Binary response profiles Parametric and nonparametric nonlinear profiles Multivariate linear profiles monitoring Statistical process control for geometric specifications Correlation and autocorrelation in profiles Nonparametric profile monitoring Throughout the book, more than two dozen real-world case studies highlight the discussed topics along with innovative examples and applications of profile monitoring. Statistical Analysis of Profile Monitoring is an excellent book for courses on statistical quality control at the graduate level. It also serves as a valuable reference for quality engineers, researchers and anyone who works in monitoring and improving statistical processes.

9823.52 РУБ

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Alfred Bartolucci Introduction to Statistical Analysis of Laboratory Data


Introduction to Statistical Analysis of Laboratory Data presents a detailed discussion of important statistical concepts and methods of data presentation and analysis Provides detailed discussions on statistical applications including a comprehensive package of statistical tools that are specific to the laboratory experiment process Introduces terminology used in many applications such as the interpretation of assay design and validation as well as “fit for purpose” procedures including real world examples Includes a rigorous review of statistical quality control procedures in laboratory methodologies and influences on capabilities Presents methodologies used in the areas such as method comparison procedures, limit and bias detection, outlier analysis and detecting sources of variation Analysis of robustness and ruggedness including multivariate influences on response are introduced to account for controllable/uncontrollable laboratory conditions

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Shelemyahu Zacks Modern Industrial Statistics. with applications in R, MINITAB and JMP


Fully revised and updated, this book combines a theoretical background with examples and references to R, MINITAB and JMP, enabling practitioners to find state-of-the-art material on both foundation and implementation tools to support their work. Topics addressed include computer-intensive data analysis, acceptance sampling, univariate and multivariate statistical process control, design of experiments, quality by design, and reliability using classical and Bayesian methods. The book can be used for workshops or courses on acceptance sampling, statistical process control, design of experiments, and reliability. Graduate and post-graduate students in the areas of statistical quality and engineering, as well as industrial statisticians, researchers and practitioners in these fields will all benefit from the comprehensive combination of theoretical and practical information provided in this single volume. Modern Industrial Statistics: With applications in R, MINITAB and JMP: Combines a practical approach with theoretical foundations and computational support. Provides examples in R using a dedicated package called MISTAT, and also refers to MINITAB and JMP. Includes exercises at the end of each chapter to aid learning and test knowledge. Provides over 40 data sets representing real-life case studies. Is complemented by a comprehensive website providing an introduction to R, and installations of JMP scripts and MINITAB macros, including effective tutorials with introductory material: www.wiley.com/go/modern_industrial_statistics.

7959.5 РУБ

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Michael Stumpf Handbook of Statistical Systems Biology


Systems Biology is now entering a mature phase in which the key issues are characterising uncertainty and stochastic effects in mathematical models of biological systems. The area is moving towards a full statistical analysis and probabilistic reasoning over the inferences that can be made from mathematical models. This handbook presents a comprehensive guide to the discipline for practitioners and educators, in providing a full and detailed treatment of these important and emerging subjects. Leading experts in systems biology and statistics have come together to provide insight in to the major ideas in the field, and in particular methods of specifying and fitting models, and estimating the unknown parameters. This book: Provides a comprehensive account of inference techniques in systems biology. Introduces classical and Bayesian statistical methods for complex systems. Explores networks and graphical modeling as well as a wide range of statistical models for dynamical systems. Discusses various applications for statistical systems biology, such as gene regulation and signal transduction. Features statistical data analysis on numerous technologies, including metabolic and transcriptomic technologies. Presents an in-depth presentation of reverse engineering approaches. Provides colour illustrations to explain key concepts. This handbook will be a key resource for researchers practising systems biology, and those requiring a comprehensive overview of this important field.

16224.03 РУБ

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John Grandfield Direct-Chill Casting of Light Alloys. Science and Technology


Direct-chill casting is the major production route for wrought aluminium and magnesium alloys that are later deformed (rolled, extruded, forged) to the final products. To aid in this process, this book provides comprehensive coverage on topics such as the history of process development in this field, industrial applications, including vertical and horizontal casting, melt preparation, fundamentals of solidification in DC casting, and more. The first book targeted for the industrial researcher and practitioner, it pulls together the practice and process of physics with the goal of improving process performance.

10935.58 РУБ

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Thomas Ryan P. Statistical Methods for Quality Improvement


Praise for the Second Edition «As a comprehensive statistics reference book for quality improvement, it certainly is one of the best books available.» —Technometrics This new edition continues to provide the most current, proven statistical methods for quality control and quality improvement The use of quantitative methods offers numerous benefits in the fields of industry and business, both through identifying existing trouble spots and alerting management and technical personnel to potential problems. Statistical Methods for Quality Improvement, Third Edition guides readers through a broad range of tools and techniques that make it possible to quickly identify and resolve both current and potential trouble spots within almost any manufacturing or nonmanufacturing process. The book provides detailed coverage of the application of control charts, while also exploring critical topics such as regression, design of experiments, and Taguchi methods. In this new edition, the author continues to explain how to combine the many statistical methods explored in the book in order to optimize quality control and improvement. The book has been thoroughly revised and updated to reflect the latest research and practices in statistical methods and quality control, and new features include: Updated coverage of control charts, with newly added tools The latest research on the monitoring of linear profiles and other types of profiles Sections on generalized likelihood ratio charts and the effects of parameter estimation on the properties of CUSUM and EWMA procedures New discussions on design of experiments that include conditional effects and fraction of design space plots New material on Lean Six Sigma and Six Sigma programs and training Incorporating the latest software applications, the author has added coverage on how to use Minitab software to obtain probability limits for attribute charts. new exercises have been added throughout the book, allowing readers to put the latest statistical methods into practice. Updated references are also provided, shedding light on the current literature and providing resources for further study of the topic. Statistical Methods for Quality Improvement, Third Edition is an excellent book for courses on quality control and design of experiments at the upper-undergraduate and graduate levels. the book also serves as a valuable reference for practicing statisticians, engineers, and physical scientists interested in statistical quality improvement.

10555.2 РУБ

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Machin David Regression Methods for Medical Research


Regression Methods for Medical Research provides medical researchers with the skills they need to critically read and interpret research using more advanced statistical methods. The statistical requirements of interpreting and publishing in medical journals, together with rapid changes in science and technology, increasingly demands an understanding of more complex and sophisticated analytic procedures. The text explains the application of statistical models to a wide variety of practical medical investigative studies and clinical trials. Regression methods are used to appropriately answer the key design questions posed and in so doing take due account of any effects of potentially influencing co-variables. It begins with a revision of basic statistical concepts, followed by a gentle introduction to the principles of statistical modelling. The various methods of modelling are covered in a non-technical manner so that the principles can be more easily applied in everyday practice. A chapter contrasting regression modelling with a regression tree approach is included. The emphasis is on the understanding and the application of concepts and methods. Data drawn from published studies are used to exemplify statistical concepts throughout. Regression Methods for Medical Research is especially designed for clinicians, public health and environmental health professionals, para-medical research professionals, scientists, laboratory-based researchers and students.

5876.99 РУБ

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Jochen Voss An Introduction to Statistical Computing. A Simulation-based Approach


A comprehensive introduction to sampling-based methods in statistical computing The use of computers in mathematics and statistics has opened up a wide range of techniques for studying otherwise intractable problems. Sampling-based simulation techniques are now an invaluable tool for exploring statistical models. This book gives a comprehensive introduction to the exciting area of sampling-based methods. An Introduction to Statistical Computing introduces the classical topics of random number generation and Monte Carlo methods. It also includes some advanced methods such as the reversible jump Markov chain Monte Carlo algorithm and modern methods such as approximate Bayesian computation and multilevel Monte Carlo techniques An Introduction to Statistical Computing: Fully covers the traditional topics of statistical computing. Discusses both practical aspects and the theoretical background. Includes a chapter about continuous-time models. Illustrates all methods using examples and exercises. Provides answers to the exercises (using the statistical computing environment R); the corresponding source code is available online. Includes an introduction to programming in R. This book is mostly self-contained; the only prerequisites are basic knowledge of probability up to the law of large numbers. Careful presentation and examples make this book accessible to a wide range of students and suitable for self-study or as the basis of a taught course

6860.88 РУБ

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Rock David Coaching with the Brain in Mind. Foundations for Practice


Coaching Brain in Mind Foundations for Practice David Rock and Linda J. Page, PhD Discover the science behind brain-based coaching By understanding how the brain works, coaching professionals can better tailor their language, strategies, and goals to be in alignment with an individuals «hard-wired» way of thinking. Written by two well-known coaching professionals, David Rock and Linda Page, Coaching with the Brain in Mind presents the tools and methodologies that can be employed by novice and experienced coaches alike to create an effective—and ultimately more rewarding—relationship for both coach and client. This informative guide to the neuroscience of coaching clearly demonstrates how brain-based coaching works in practice, and how the power of the mind can be harnessed to help an individual learn and grow. Illustrated with numerous case examples and stories, this book is organized for immediate use by professionals in their client work. Coverage includes: A succinct but comprehensive overview of the major scientific and theoretical foundations for coaching and their implications for practice How the language of coaching—setting goals, making connections, becoming more aware, seeking breakthroughs, and taking action—parallels what neuroscientists tell us about how the brain operates Neuroscience as a natural platform for the ongoing development of coaching Building on the existing foundation of coaching by adding neuroscience as an evidence base for the profession, Coaching with the Brain in Mind shows that it is possible to become a better professional coach by understanding how the brain works. As well, the authors, through their research, present that an understanding of neuroscience research, however new and speculative, can help coaches and leaders fulfill their potential as change agents in the lives of others.

4825.24 РУБ

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Glass V. Glass, Victor L. Willson, John M. Gottman Design and Analysis of Time-Series Experiments (PB)


Hailed as a landmark in the development of experimental methods when itappeared in 1975, Design and Analysis of Time-Series Experiments is availableagain after several years of being out of print.Gene V Glass, Victor L. Willson and John M. Gottman have carried forward thedesign and analysis of perhaps the most powerful and useful quasi-experimentaldesign identified by their mentors in the classic Campbell & Stanley text Experimental and Quasi-experimentalDesign for Research (1966). In an era when governments seek to resolve questions of experimental validity byfiat and the label "Scientifically Based Research" is appropriated for only certain privileged experimentaldesigns, nothing could be more appropriate than to bring back the classic text that challenges doctrinaireopinions of proper causal analysis.Glass, Willson & Gottman introduce and illustrate an armamentarium of interrupted time-series experimentaldesigns that offer some of the most powerful tools for discovering andvalidating causal relationships in social and education policy analysis.Drawing on the ground-breaking statistical analytic tools of Box & Jenkins,the authors extend the comprehensive autoregressive-integrated-movingaverages(ARIMA) model to accommodate significance testing andestimation of the effects of interventions into real world time-series. Designsand full statistical analyses are richly illustrated with actual examples fromeducation, behavioral psychology, and sociology.

6277 РУБ

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Gerald Hahn J. Statistical Intervals. A Guide for Practitioners and Researchers


Describes statistical intervals to quantify sampling uncertainty,focusing on key application needs and recently developed methodology in an easy-to-apply format Statistical intervals provide invaluable tools for quantifying sampling uncertainty. The widely hailed first edition, published in 1991, described the use and construction of the most important statistical intervals. Particular emphasis was given to intervals—such as prediction intervals, tolerance intervals and confidence intervals on distribution quantiles—frequently needed in practice, but often neglected in introductory courses. Vastly improved computer capabilities over the past 25 years have resulted in an explosion of the tools readily available to analysts. This second edition—more than double the size of the first—adds these new methods in an easy-to-apply format. In addition to extensive updating of the original chapters, the second edition includes new chapters on: Likelihood-based statistical intervals Nonparametric bootstrap intervals Parametric bootstrap and other simulation-based intervals An introduction to Bayesian intervals Bayesian intervals for the popular binomial, Poisson and normal distributions Statistical intervals for Bayesian hierarchical models Advanced case studies, further illustrating the use of the newly described methods New technical appendices provide justification of the methods and pathways to extensions and further applications. A webpage directs readers to current readily accessible computer software and other useful information. Statistical Intervals: A Guide for Practitioners and Researchers, Second Edition is an up-to-date working guide and reference for all who analyze data, allowing them to quantify the uncertainty in their results using statistical intervals.

8186.15 РУБ

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Deena Katz B. Katzs Complete Guide to Practice Management. Tips, Tools, and Templates for the Financial Adviser


Deena B. Katz, CFP, a preeminent authority on practice management and an internationally recognized financial adviser, presents a comprehensive guide to running a professional financial planning practice. To create this book, Katz updated, revised, and combined her two acclaimed books Deena Katz on Practice Management (1999) and Deena Katzs Tools and Templates for Your Practice (2001). In this newly expanded volume, she presents the essentials on how to help a practice thrive side by side with the tools and templates needed for the everyday operation of your firm. This new volume offers guidance on practice-management issues: setting up an office systems and technology administration and staffing marketing growing as the market changes hanging on to clients for the long term succession planning when the time comes This comprehensive resource provides sample forms, worksheets, templates, letters, brochures, and collateral materials developed and refined by top wealth managers and planners. From keeping the business running well by designing dynamic collateral material, to considering plans for retirement, Deena B. Katz guides advisers through every challenge a financial planning business will face.

4712.15 РУБ

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B. L. S. Prakasa Rao Statistical Inference for Fractional Diffusion Processes


Stochastic processes are widely used for model building in the social, physical, engineering and life sciences as well as in financial economics. In model building, statistical inference for stochastic processes is of great importance from both a theoretical and an applications point of view. This book deals with Fractional Diffusion Processes and statistical inference for such stochastic processes. The main focus of the book is to consider parametric and nonparametric inference problems for fractional diffusion processes when a complete path of the process over a finite interval is observable. Key features: Introduces self-similar processes, fractional Brownian motion and stochastic integration with respect to fractional Brownian motion. Provides a comprehensive review of statistical inference for processes driven by fractional Brownian motion for modelling long range dependence. Presents a study of parametric and nonparametric inference problems for the fractional diffusion process. Discusses the fractional Brownian sheet and infinite dimensional fractional Brownian motion. Includes recent results and developments in the area of statistical inference of fractional diffusion processes. Researchers and students working on the statistics of fractional diffusion processes and applied mathematicians and statisticians involved in stochastic process modelling will benefit from this book.

9725.87 РУБ

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B. L. S. Prakasa Rao Statistical Inference for Fractional Diffusion Processes


Stochastic processes are widely used for model building in the social, physical, engineering and life sciences as well as in financial economics. In model building, statistical inference for stochastic processes is of great importance from both a theoretical and an applications point of view. This book deals with Fractional Diffusion Processes and statistical inference for such stochastic processes. The main focus of the book is to consider parametric and nonparametric inference problems for fractional diffusion processes when a complete path of the process over a finite interval is observable. Key features: Introduces self-similar processes, fractional Brownian motion and stochastic integration with respect to fractional Brownian motion. Provides a comprehensive review of statistical inference for processes driven by fractional Brownian motion for modelling long range dependence. Presents a study of parametric and nonparametric inference problems for the fractional diffusion process. Discusses the fractional Brownian sheet and infinite dimensional fractional Brownian motion. Includes recent results and developments in the area of statistical inference of fractional diffusion processes. Researchers and students working on the statistics of fractional diffusion processes and applied mathematicians and statisticians involved in stochastic process modelling will benefit from this book.

9725.87 РУБ

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Arben Merkoci Biosensing Using Nanomaterials


An interdisciplinary approach to one of the hottest topics in nanotechnology and nanoscience Biosensing Using Nanomaterials introduces novel concepts in the area of bioanalysis based on nanomaterials, opening new opportunities for basic research and new tools for real bioanalytical applications. In fifteen chapters, readers are introduced to the most successful nanomaterials used so far in biosensing, including carbon nanotubes, nanoparticles, and nanochannels. Each chapter provides a theoretical overview of the topic, a discussion of the published data relating to the bioanalytical system, and a selected list of references for further investigation. The result is a book that provides a comprehensive forum of interest to scientists, engineers, researchers, manufacturers, teachers, and students. Biosensing Using Nanomaterials is an important resource for a broad audience involved in the research, teaching, learning, and practice of integrating nanomaterials into biosensing systems for clinical, environmental, and industrial applications.

14701.89 РУБ

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Jennifer Hoeting A. Computational Statistics


This new edition continues to serve as a comprehensive guide to modern and classical methods of statistical computing. The book is comprised of four main parts spanning the field: Optimization Integration and Simulation Bootstrapping Density Estimation and Smoothing Within these sections,each chapter includes a comprehensive introduction and step-by-step implementation summaries to accompany the explanations of key methods. The new edition includes updated coverage and existing topics as well as new topics such as adaptive MCMC and bootstrapping for correlated data. The book website now includes comprehensive R code for the entire book. There are extensive exercises, real examples, and helpful insights about how to use the methods in practice.

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