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Statistical Thinking: Improving Business Performance (Wiley and SAS Business Series #58)
by Roger W. Hoerl Ronald D. SneeApply statistics in business to achieve performance improvement Statistical Thinking: Improving Business Performance, 3rd Edition helps managers understand the role of statistics in implementing business improvements. It guides professionals who are learning statistics in order to improve performance in business and industry. It also helps graduate and undergraduate students understand the strategic value of data and statistics in arriving at real business solutions. Instruction in the book is based on principles of effective learning, established by educational and behavioral research. The authors cover both practical examples and underlying theory, both the big picture and necessary details. Readers gain a conceptual understanding and the ability to perform actionable analyses. They are introduced to data skills to improve business processes, including collecting the appropriate data, identifying existing data limitations, and analyzing data graphically. The authors also provide an in-depth look at JMP software, including its purpose, capabilities, and techniques for use. Updates to this edition include: A new chapter on data, assessing data pedigree (quality), and acquisition tools Discussion of the relationship between statistical thinking and data science Explanation of the proper role and interpretation of p-values (understanding of the dangers of “p-hacking”) Differentiation between practical and statistical significance Introduction of the emerging discipline of statistical engineering Explanation of the proper role of subject matter theory in order to identify causal relationships A holistic framework for variation that includes outliers, in addition to systematic and random variation Revised chapters based on significant teaching experience Content enhancements based on student input This book helps readers understand the role of statistics in business before they embark on learning statistical techniques.
Statistical Thinking
by Ron D. Snee Roger HoerlHow statistical thinking and methodology can help you make crucial business decisionsStraightforward and insightful, Statistical Thinking: Improving Business Performance, Second Edition, prepares you for business leadership by developing your capacity to apply statistical thinking to improve business processes. Unique and compelling, this book shows you how to derive actionable conclusions from data analysis, solve real problems, and improve real processes. Here, you'll discover how to implement statistical thinking and methodology in your work to improve business performance.Explores why statistical thinking is necessary and helpfulProvides case studies that illustrate how to integrate several statistical tools into the decision-making processFacilitates and encourages an experiential learning environment to enable you to apply material to actual problemsWith an in-depth discussion of JMP® software, the new edition of this important book focuses on skills to improve business processes, including collecting data appropriate for a specified purpose, recognizing limitations in existing data, and understanding the limitations of statistical analyses.
Statistical Thinking for Non-Statisticians in Drug Regulation
by Richard KaySTATISTICAL THINKING FOR NON-STATISTICIANS IN DRUG REGULATION Statistical methods in the pharmaceutical industry are accepted as a key element in the design and analysis of clinical studies. Increasingly, the medical and scientific community are aligning with the regulatory authorities and recognizing that correct statistical methodology is essential as the basis for valid conclusions. In order for those correct and robust methods to be successfully employed there needs to be effective communication across disciplines at all stages of the planning, conducting, analyzing and reporting of clinical studies associated with the development and evaluation of new drugs and devices. Statistical Thinking for Non-Statisticians in Drug Regulation provides a comprehensive in-depth guide to statistical methodology for pharmaceutical industry professionals, including physicians, investigators, medical science liaisons, clinical research scientists, medical writers, regulatory personnel, statistical programmers, senior data managers and those working in pharmacovigilance. The author’s years of experience and up-to-date familiarity with pharmaceutical regulations and statistical practice within the wider clinical community make this an essential guide for the those working in and with the industry. The third edition of Statistical Thinking for Non-Statisticians in Drug Regulation includes: A detailed new chapter on Estimands in line with the 2019 Addendum to ICH E9 Major new sections on topics including Combining Hierarchical Testing and Alpha Adjustment, Biosimilars, Restricted Mean Survival Time, Composite Endpoints and Cumulative Incidence Functions, Adjusting for Cross-Over in Oncology, Inverse Propensity Score Weighting, and Network Meta-Analysis Updated coverage of many existing topics to reflect new and revised guidance from regulatory authorities and author experience Statistical Thinking for Non-Statisticians in Drug Regulation is a valuable guide for pharmaceutical and medical device industry professionals, as well as statisticians joining the pharmaceutical industry and students and teachers of drug development.
Statistical Thinking in Business
by null J. A. John null D. WhitakerBusiness students need the ability to think statistically about how to deal with uncertainty and its effect on decision-making in business and management. Traditional statistics courses and textbooks tend to focus on probability, mathematical detail, and heavy computation, and thus fail to meet the needs of future managers. Statistical Thinking in Business, Second Edition responds to the growing recognition that we must change the way business statistics is taught. It shows how statistics is important in all aspects of business and equips students with the skills they need to make sensible use of data and other information. The authors take an interactive, scenario-based approach and use almost no mathematical formulas, opting to use Excel for the technical work. This allows them to focus on using statistics to aid decision-making rather than how to perform routine calculations.New in the Second Edition A completely revised chapter on forecasting Re-arrangement of the material on data presentation with the inclusion of histograms and cumulative line plots A more thorough discussion of the analysis of attribute data Coverage of variable selection and model building in multiple regression End-of-chapter summaries More end-of-chapter problems A variety of case studies throughout the book The second edition also comes with a wealth of ancillary materials provided on downloadable resources packaged with the book. These include automatically-marked multiple-choice questions, answers to questions in the text, data sets, Excel experiments and demonstrations, an introduction to Excel, and the StiBstat Add-In for stem and leaf plots, box plots, distribution plots, control charts and summary statistics.
Statistical Thinking in Clinical Trials (Chapman & Hall/CRC Biostatistics Series)
by Michael A. ProschanStatistical Thinking in Clinical Trials combines a relatively small number of key statistical principles and several instructive clinical trials to gently guide the reader through the statistical thinking needed in clinical trials. Randomization is the cornerstone of clinical trials and randomization-based inference is the cornerstone of this book. Read this book to learn the elegance and simplicity of re-randomization tests as the basis for statistical inference (the analyze as you randomize principle) and see how re-randomization tests can save a trial that required an unplanned, mid-course design change. Other principles enable the reader to quickly and confidently check calculations without relying on computer programs. The `EZ’ principle says that a single sample size formula can be applied to a multitude of statistical tests. The `O minus E except after V’ principle provides a simple estimator of the log odds ratio that is ideally suited for stratified analysis with a binary outcome. The same principle can be used to estimate the log hazard ratio and facilitate stratified analysis in a survival setting. Learn these and other simple techniques that will make you an invaluable clinical trial statistician.
Statistical Thinking in Epidemiology
by Yu-Kang Tu Mark GilthorpeWhile biomedical researchers may be able to follow instructions in the manuals accompanying the statistical software packages, they do not always have sufficient knowledge to choose the appropriate statistical methods and correctly interpret their results. Statistical Thinking in Epidemiology examines common methodological and statistical problems
Statistical Thinking in Sports
by Jim Albert Ruud H. KoningSince the first athletic events found a fan base, sports and statistics have always maintained a tight and at times mythical relationship. As a way to relay the telling of a game's drama and attest to the prodigious powers of the heroes involved, those reporting on the games tallied up the numbers that they believe best described the action and bes
Statistical Tools for Environmental Quality Measurement (Chapman & Hall/CRC Applied Environmental Statistics)
by null Douglas E. Splitstone null Michael E. GinevanWhen interpreting environmental data, scientists and engineers first must select the correct statistical tool to use for their analysis. By doing this they will be able to make sound decisions in their efforts to solve environmental problems. They need a detailed reference that points out the subtle differences between statistical procedures, makin
Statistical Tools for Measuring Agreement
by Wenting Wu Lawrence Lin A. S. HedayatAgreement assessment techniques are widely used in examining the acceptability of a new or generic process, methodology and/or formulation in areas of lab performance, instrument/assay validation or method comparisons, statistical process control, goodness-of-fit, and individual bioequivalence. Successful applications in these situations require a sound understanding of both the underlying theory and methodological advances in handling real-life problems. This book seeks to effectively blend theory and applications while presenting readers with many practical examples. For instance, in the medical device environment, it is important to know if the newly established lab can reproduce the instrument/assay results from the established but outdating lab. When there is a disagreement, it is important to differentiate the sources of disagreement. In addition to agreement coefficients, accuracy and precision coefficients are introduced and utilized to characterize these sources. This book will appeal to a broad range of statisticians, researchers, practitioners and students, in areas of biomedical devices, psychology, medical research, and others, in which agreement assessment are needed. Many practical illustrative examples will be presented throughout the book in a wide variety of situations for continuous and categorical data.
Statistical Tools for Program Evaluation: Methods and Applications to Economic Policy, Public Health, and Education
by Jean-Michel Josselin Benoît Le MauxThis book provides a self-contained presentation of the statistical tools required for evaluating public programs, as advocated by many governments, the World Bank, the European Union, and the Organization for Economic Cooperation and Development. After introducing the methodological framework of program evaluation, the first chapters are devoted to the collection, elementary description and multivariate analysis of data as well as the estimation of welfare changes. The book then successively presents the tools of ex-ante methods (financial analysis, budget planning, cost-benefit, cost-effectiveness and multi-criteria evaluation) and ex-post methods (benchmarking, experimental and quasi-experimental evaluation). The step-by-step approach and the systematic use of numerical illustrations equip readers to handle the statistics of program evaluation. It not only offers practitioners from public administrations, consultancy firms and nongovernmental organizations the basic tools and advanced techniques used in program assessment, it is also suitable for executive management training, upper undergraduate and graduate courses, as well as for self-study.
Statistical Topics and Stochastic Models for Dependent Data with Applications
by Vlad Stefan Barbu Nicolas VergneThis book is a collective volume authored by leading scientists in the field of stochastic modelling, associated statistical topics and corresponding applications. The main classes of stochastic processes for dependent data investigated throughout this book are Markov, semi-Markov, autoregressive and piecewise deterministic Markov models. The material is divided into three parts corresponding to: (i) Markov and semi-Markov processes, (ii) autoregressive processes and (iii) techniques based on divergence measures and entropies. A special attention is payed to applications in reliability, survival analysis and related fields.
Statistical Topics in Health Economics and Outcomes Research (Chapman & Hall/CRC Biostatistics Series)
by Demissie Alemayehu Joseph C. Cappelleri Birol Emir Kelly H. ZouWith ever-rising healthcare costs, evidence generation through Health Economics and Outcomes Research (HEOR) plays an increasingly important role in decision-making about the allocation of resources. Accordingly, it is now customary for health technology assessment and reimbursement agencies to request for HEOR evidence, in addition to data from clinical trials, to inform decisions about patient access to new treatment options. While there is a great deal of literature on HEOR, there is a need for a volume that presents a coherent and unified review of the major issues that arise in application, especially from a statistical perspective. Statistical Topics in Health Economics and Outcomes Research fulfils that need by presenting an overview of the key analytical issues and best practice. Special attention is paid to key assumptions and other salient features of statistical methods customarily used in the area, and appropriate and relatively comprehensive references are made to emerging trends. The content of the book is purposefully designed to be accessible to readers with basic quantitative backgrounds, while providing an in-depth coverage of relatively complex statistical issues. The book will make a very useful reference for researchers in the pharmaceutical industry, academia, and research institutions involved with HEOR studies. The targeted readers may include statisticians, data scientists, epidemiologists, outcomes researchers, health economists, and healthcare policy and decision-makers.
Statistical Treatment of Experimental Data
by Hugh D. YoungDealing with statistical treatment of experimental data, this text covers topics such as errors, probability, the binomial distribution, the Poisson distribution, the Gauss distribution, method of least squares and standard deviation of the mean.
Statistical Universals of Language: Mathematical Chance vs. Human Choice (Mathematics in Mind)
by Kumiko Tanaka-IshiiThis volume explores the universal mathematical properties underlying big language data and possible reasons why such properties exist, revealing how we may be unconsciously mathematical in our language use. These properties are statistical and thus different from linguistic universals that contribute to describing the variation of human languages, and they can only be identified over a large accumulation of usages. The book provides an overview of state-of-the art findings on these statistical universals and reconsiders the nature of language accordingly, with Zipf's law as a well-known example.The main focus of the book further lies in explaining the property of long memory, which was discovered and studied more recently by borrowing concepts from complex systems theory. The statistical universals not only possibly lie as the precursor of language system formation, but they also highlight the qualities of language that remain weak points in today's machine learning.In summary, this book provides an overview of language's global properties. It will be of interest to anyone engaged in fields related to language and computing or statistical analysis methods, with an emphasis on researchers and students in computational linguistics and natural language processing. While the book does apply mathematical concepts, all possible effort has been made to speak to a non-mathematical audience as well by communicating mathematical content intuitively, with concise examples taken from real texts.
Statistically Speaking: A Dictionary of Quotations
by C.C. GaitherStatistically Speaking is a book of quotations. It brings together the best expressed thoughts that are especially illuminating and pertinent to the disciplines of probability and statistics. The book is an aid for the individual who loves to quote – and to quote correctly.
Statistics: The Art and Science of Learning from Data (2nd Edition)
by Alan Agresti Christine FranklinAlan Agresti and Chris Franklin have merged their research and classroom experience to develop this successful introductory statistics text. Statistics: The Art and Science of Learning from Data, Second Edition helps readers become statistically literate by encouraging them to ask and answer interesting statistical questions. It takes the ideas that have turned statistics into a central science in modern life and makes them accessible and engaging to readers without compromising necessary rigor.
Statistics: The Art and Science of Learning from Data (Fourth Edition)
by Alan Agresti Christine Franklin Bernhard KlingenbergThe fourth edition of this textbook aims at improving the student and instructor user experience to learn statistics from the traditional formula-driven mathematical statistics course to a concept-driven approach. This concept-driven approach places more emphasis on why statistics is important in the real world and places less emphasis on mathematical probability. The book aims to help students make the conceptual approach more interesting and more readily accessible.
Statistics: A Guide to the Use of Statistical Methods in the Physical Sciences (Manchester Physics Series #29)
by R. J. BarlowThe Manchester Physics Series General Editors: D. J. Sandiford; F. Mandl; A. C. Phillips Department of Physics and Astronomy, University of Manchester Properties of Matter B. H. Flowers and E. Mendoza Optics Second Edition F. G. Smith and J. H. Thomson Statistical Physics Second Edition F. Mandl Electromagnetism Second Edition I. S. Grant and W. R. Phillips Statistics R. J. Barlow Solid State Physics Second Edition J. R. Hook and H. E. Hall Quantum Mechanics F. Mandl Particle Physics Second Edition B. R. Martin and G. Shaw The Physics of Stars Second Edition A.C. Phillips Computing for Scientists R. J. Barlow and A. R. Barnett Written by a physicist, Statistics is tailored to the needs of physical scientists, containing and explaining all they need to know. It concentrates on parameter estimation, especially the methods of Least Squares and Maximum Likelihood, but other techniques, such as hypothesis testing, Bayesian statistics and non-parametric methods are also included. Intended for reasonably numerate scientists it contains all the basic formulae, their derivations and applications, together with some more advanced ones. Statistics features: * Comprehensive coverage of the essential techniques physical scientists are likely to need. * A wealth of examples, and problems with their answers. * Flexible structure and organisation allows it to be used as a course text and a reference. * A review of the basics, so that little prior knowledge is required.
Statistics: A Gentle Introduction
by Frederick L. CoolidgeDoing statistics for the first time? Don't panic says Professor Fred Coolidge. In Statistics: A Gentle Introduction, Second Edition, he shows how statistics needn't be difficult or dull. Dr. Coolidge likens the role of a statistician to that of a curious detective, an honest attorney, and a good storyteller. He minimizes the use of formulas, but provides a step-by-step approach to their solution, and includes a glossary of key terms, symbols, and definitions at the end of each chapter. Every chapter also includes a short story about historical and contemporary statisticians who figured prominently in the evolution of the discipline of statistics. This second edition includes specific suggestions as to the detection of baloney, that is, fraudulent claims and questionable studies.
Statistics: A Gentle Introduction (3rd Edition)
by Frederick L. CoolidgeWith Statistics: A Gentle Introduction, Third Edition, an introductory stats class needn't be difficult or dull! Frederick L. Coolidge specifically designed his text to curtail students' anxieties and minimize unnecessary formulas, while providing a comprehensive review of basic statistical designs and analyses. A wealth of additional real-world examples have been included to give a sense of how the science of statistics works, solves problems, and helps us make informed choices about the world we live in. The author minimizes the use of formulas, but provides a step-by-step approach to their solution, and includes a glossary of key terms, symbols, and definitions at the end of each chapter. Every chapter also includes a short story about historical and contemporary statisticians who figured prominently in the evolution of the discipline of statistics. New to the Third Edition is the thorough incorporation of SPSS throughout, more visual material and figures, and an enhanced treatment of effect sizes, and more detailed explanation of statistical concepts.
Statistics: A Gentle Introduction
by Frederick L. CoolidgeThe Fourth Edition of Statistics: A Gentle Introduction shows students that an introductory statistics class doesn’t need to be difficult or dull. This text minimizes students’ anxieties about math by explaining the concepts of statistics in plain language first, before addressing the math. Each formula within the text has a step-by-step example to demonstrate the calculation so students can follow along. Only those formulas that are important for final calculations are included in the text so students can focus on the concepts, not the numbers. A wealth of real-world examples and applications gives a context for statistics in the real world and how it helps us solve problems and make informed choices. New to the Fourth Edition are sections on working with big data, new coverage of alternative non-parametric tests, beta coefficients, and the "nocebo effect," discussions of p values in the context of research, an expanded discussion of confidence intervals, and more exercises and homework options under the new feature "Test Yourself." Included with this title: The password-protected Instructor Resource Site (formally known as SAGE Edge) offers access to all text-specific resources, including a test bank and editable, chapter-specific PowerPoint® slides.
Statistics: A Gentle Introduction
by Frederick L. CoolidgeThe Fourth Edition of Statistics: A Gentle Introduction shows students that an introductory statistics class doesn’t need to be difficult or dull. This text minimizes students’ anxieties about math by explaining the concepts of statistics in plain language first, before addressing the math. Each formula within the text has a step-by-step example to demonstrate the calculation so students can follow along. Only those formulas that are important for final calculations are included in the text so students can focus on the concepts, not the numbers. A wealth of real-world examples and applications gives a context for statistics in the real world and how it helps us solve problems and make informed choices. New to the Fourth Edition are sections on working with big data, new coverage of alternative non-parametric tests, beta coefficients, and the "nocebo effect," discussions of p values in the context of research, an expanded discussion of confidence intervals, and more exercises and homework options under the new feature "Test Yourself." Included with this title: The password-protected Instructor Resource Site (formally known as SAGE Edge) offers access to all text-specific resources, including a test bank and editable, chapter-specific PowerPoint® slides.
Statistics: An Introduction Using R
by Michael J. Crawley"...I know of no better book of its kind..." (Journal of the Royal Statistical Society, Vol 169 (1), January 2006) A revised and updated edition of this bestselling introductory textbook to statistical analysis using the leading free software package R This new edition of a bestselling title offers a concise introduction to a broad array of statistical methods, at a level that is elementary enough to appeal to a wide range of disciplines. Step-by-step instructions help the non-statistician to fully understand the methodology. The book covers the full range of statistical techniques likely to be needed to analyse the data from research projects, including elementary material like t--tests and chi--squared tests, intermediate methods like regression and analysis of variance, and more advanced techniques like generalized linear modelling. Includes numerous worked examples and exercises within each chapter.
Statistics
by Robert A. Donnelly Fatma Abdel-RaoufStatistics is a class that is required in many college majors, and it's an increasingly popular Advanced Placement (AP) high school course. In addition to math and technical students, many business and liberal arts students are required to take it as a fundamental component of their majors. A knowledge of statistical interpretation is vital for many careers. Idiot's Guides(R) Statistics explains the fundamental tenets in language anyone can understand.
Statistics: 1,001 Practice Problems For Dummies (+ Free Online Practice)
by Consumer Dummies1,001 practice opportunities to score higher in statistics 1,001 Statistics Practice Problems For Dummies takes you beyond the instruction and guidance offered in Statistics For Dummies to give you a more hands-on understanding of statistics. The practice problems offered range in difficulty, including detailed explanations and walk-throughs. In this series, every step of every solution is shown with explanations and detailed narratives to help you solve each problem. With the book purchase, you'll also get access to practice statistics problems online. This content features 1,001 practice problems presented in multiple choice format; on-the-go access from smart phones, computers, and tablets; customizable practice sets for self-directed study; practice problems categorized as easy, medium, or hard; and a one-year subscription with book purchase. Offers on-the-go access to practice statistics problems Gives you friendly, hands-on instruction 1,001 statistics practice problems that range in difficulty 1,001 Statistics Practice Problems For Dummies provides ample practice opportunities for students who may have taken statistics in high school and want to review the most important concepts as they gear up for a faster-paced college class.