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Statistical Case Studies
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Book Synopsis Statistical Case Studies by : Roxy Peck
Download or read book Statistical Case Studies written by Roxy Peck and published by SIAM. This book was released on 1998-01-01 with total page 308 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statisticians know that the clean data sets that appear in textbook problems have little to do with real-life industry data. To better prepare their students for all types of statistical careers, academic statisticians now strive to use data sets from real-life statistical problems. This book contains 20 case studies that use actual data sets that have not been simplified for classroom use. Each case study is a collaboration between statisticians from academe and from business, industry, or government. This book is the result of a collaborative workshop of statisticians focusing on academic-industrial partnerships. The cases come from a wide variety of application areas, including biology/environment, medical and health care, pharmaceutical, marketing and survey research, and manufacturing.
Book Synopsis Case Studies in Data Analysis by : Jane F. Gentleman
Download or read book Case Studies in Data Analysis written by Jane F. Gentleman and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 270 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume is a collection of eight Case Studies in Data Analysis that appeared in various issues of the Canadian Journal of Statistics (OS) over a twelve year period from 1982 to 1993. One follow-up article to Case Study No.4 is also included in the volume. The OS's Section on Case Studies in Data Analysis was initiated by a former editor who wanted to increase the analytical content of the journal. We were asked to become Section Co-Editors and to develop a format for the case studies. Each case study presents analyses of a real data set by two or more analysts or teams of analysts working independently in a simulated consulting context. The section aimed at demonstrating the process of statistical analysis and the possible diversity of approaches and conclusions. For each case study, the Co-Editors found a set of real Canadian data, posed what they thought was an interesting statistical problem, and recruited analysts working in Canada who were willing to tackle it. The published case studies describe the data and the problem, and present and discuss the analysts' solutions. For some case studies, the providers of the data were invited to contribute their own analysis.
Book Synopsis Statistical Case Studies for Industrial Process Improvement by : Veronica Czitrom
Download or read book Statistical Case Studies for Industrial Process Improvement written by Veronica Czitrom and published by SIAM. This book was released on 1997-01-01 with total page 510 pages. Available in PDF, EPUB and Kindle. Book excerpt: A selection of studies by professionals in the semiconductor industry illustrating the use of statistical methods to improve manufacturing processes.
Book Synopsis Statistical Case Studies by : Roxy Peck
Download or read book Statistical Case Studies written by Roxy Peck and published by SIAM. This book was released on 1998-01-01 with total page 212 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statisticians know that the clean data sets that appear in textbook problems have little to do with real-life industry data. To better prepare their students for all types of statistical careers, academic statisticians now strive to use data sets from real-life statistical problems. This book contains 20 case studies that use actual data sets that have not been simplified for classroom use. Each case study is a collaboration between statisticians from academe and from business, industry, or government.
Book Synopsis Statistical Case Studies by : Roxy Peck
Download or read book Statistical Case Studies written by Roxy Peck and published by SIAM. This book was released on 1998-01-01 with total page 308 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book contains 20 case studies that use actual data sets that have not been simplified for classroom use.
Book Synopsis Statistical Case Studies for Industrial Process Improvement by : Veronica Czitrom
Download or read book Statistical Case Studies for Industrial Process Improvement written by Veronica Czitrom and published by SIAM. This book was released on 1997-01-01 with total page 541 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book contains a broad selection of case studies written by professionals in the semiconductor industry that illustrate the use of statistical methods to improve manufacturing processes. These case studies offer engineers, scientists, technicians, and managers numerous examples of best-in-class practices by their peers. Because of the universal nature of statistical applications, the methods described here can be applied to a wide range of industries, including the chemical, biotechnology, automotive, steel, plastics, textile, and food industries. Many industries already benefit from the use of statistical methods, although the semiconductor industry is considered both a leader in and a model for the wide application and effective use of statistics.
Book Synopsis Handbook of Statistical Methods for Case-Control Studies by : Ørnulf Borgan
Download or read book Handbook of Statistical Methods for Case-Control Studies written by Ørnulf Borgan and published by CRC Press. This book was released on 2018-06-27 with total page 700 pages. Available in PDF, EPUB and Kindle. Book excerpt: Handbook of Statistical Methods for Case-Control Studies is written by leading researchers in the field. It provides an in-depth treatment of up-to-date and currently developing statistical methods for the design and analysis of case-control studies, as well as a review of classical principles and methods. The handbook is designed to serve as a reference text for biostatisticians and quantitatively-oriented epidemiologists who are working on the design and analysis of case-control studies or on related statistical methods research. Though not specifically intended as a textbook, it may also be used as a backup reference text for graduate level courses. Book Sections Classical designs and causal inference, measurement error, power, and small-sample inference Designs that use full-cohort information Time-to-event data Genetic epidemiology About the Editors Ørnulf Borgan is Professor of Statistics, University of Oslo. His book with Andersen, Gill and Keiding on counting processes in survival analysis is a world classic. Norman E. Breslow was, at the time of his death, Professor Emeritus in Biostatistics, University of Washington. For decades, his book with Nick Day has been the authoritative text on case-control methodology. Nilanjan Chatterjee is Bloomberg Distinguished Professor, Johns Hopkins University. He leads a broad research program in statistical methods for modern large scale biomedical studies. Mitchell H. Gail is a Senior Investigator at the National Cancer Institute. His research includes modeling absolute risk of disease, intervention trials, and statistical methods for epidemiology. Alastair Scott was, at the time of his death, Professor Emeritus of Statistics, University of Auckland. He was a major contributor to using survey sampling methods for analyzing case-control data. Chris J. Wild is Professor of Statistics, University of Auckland. His research includes nonlinear regression and methods for fitting models to response-selective data.
Book Synopsis Statistical Decision Problems by : Michael Zabarankin
Download or read book Statistical Decision Problems written by Michael Zabarankin and published by Springer Science & Business Media. This book was released on 2013-12-16 with total page 254 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistical Decision Problems presents a quick and concise introduction into the theory of risk, deviation and error measures that play a key role in statistical decision problems. It introduces state-of-the-art practical decision making through twenty-one case studies from real-life applications. The case studies cover a broad area of topics and the authors include links with source code and data, a very helpful tool for the reader. In its core, the text demonstrates how to use different factors to formulate statistical decision problems arising in various risk management applications, such as optimal hedging, portfolio optimization, cash flow matching, classification, and more. The presentation is organized into three parts: selected concepts of statistical decision theory, statistical decision problems, and case studies with portfolio safeguard. The text is primarily aimed at practitioners in the areas of risk management, decision making, and statistics. However, the inclusion of a fair bit of mathematical rigor renders this monograph an excellent introduction to the theory of general error, deviation, and risk measures for graduate students. It can be used as supplementary reading for graduate courses including statistical analysis, data mining, stochastic programming, financial engineering, to name a few. The high level of detail may serve useful to applied mathematicians, engineers, and statisticians interested in modeling and managing risk in various applications.
Book Synopsis Case Studies in Bayesian Statistical Modelling and Analysis by : Clair L. Alston
Download or read book Case Studies in Bayesian Statistical Modelling and Analysis written by Clair L. Alston and published by John Wiley & Sons. This book was released on 2012-12-17 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Provides an accessible foundation to Bayesian analysis using real world models This book aims to present an introduction to Bayesian modelling and computation, by considering real case studies drawn from diverse fields spanning ecology, health, genetics and finance. Each chapter comprises a description of the problem, the corresponding model, the computational method, results and inferences as well as the issues that arise in the implementation of these approaches. Case Studies in Bayesian Statistical Modelling and Analysis: Illustrates how to do Bayesian analysis in a clear and concise manner using real-world problems. Each chapter focuses on a real-world problem and describes the way in which the problem may be analysed using Bayesian methods. Features approaches that can be used in a wide area of application, such as, health, the environment, genetics, information science, medicine, biology, industry and remote sensing. Case Studies in Bayesian Statistical Modelling and Analysis is aimed at statisticians, researchers and practitioners who have some expertise in statistical modelling and analysis, and some understanding of the basics of Bayesian statistics, but little experience in its application. Graduate students of statistics and biostatistics will also find this book beneficial.
Book Synopsis Introduction to Statistical Thinking by : Benjamin Yakir
Download or read book Introduction to Statistical Thinking written by Benjamin Yakir and published by . This book was released on 2014-09-19 with total page 324 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introduction to Statistical ThinkingBy Benjamin Yakir
Book Synopsis Public Policy and Statistics by : Sally C. Morton
Download or read book Public Policy and Statistics written by Sally C. Morton and published by Springer Science & Business Media. This book was released on 2000-05-19 with total page 260 pages. Available in PDF, EPUB and Kindle. Book excerpt: A critical yet constructive description of the rich analytical techniques and substantive applications that typify how statistical thinking has been applied at the RAND Corporation over the past two decades. Case studies of public policy problems are useful for teaching because they are familiar: almost everyone knows something abut health insurance, global warming, and capital punishment, to name but a few of the applications covered in this casebook. Each case study has a common format that describes the policy questions, the statistical questions, and the successful and the unsuccessful analytic strategies. Readers should be familiar with basic statistical concepts including sampling and regression. While designed for statistics courses in areas ranging from economics to health policy to the law at both the advanced undergraduate and graduate levels, empirical researchers and policy-makers will also find this casebook informative.
Book Synopsis The Analysis of Covariance and Alternatives by : Bradley Huitema
Download or read book The Analysis of Covariance and Alternatives written by Bradley Huitema and published by John Wiley & Sons. This book was released on 2011-10-24 with total page 562 pages. Available in PDF, EPUB and Kindle. Book excerpt: A complete guide to cutting-edge techniques and best practices for applying covariance analysis methods The Second Edition of Analysis of Covariance and Alternatives sheds new light on its topic, offering in-depth discussions of underlying assumptions, comprehensive interpretations of results, and comparisons of distinct approaches. The book has been extensively revised and updated to feature an in-depth review of prerequisites and the latest developments in the field. The author begins with a discussion of essential topics relating to experimental design and analysis, including analysis of variance, multiple regression, effect size measures and newly developed methods of communicating statistical results. Subsequent chapters feature newly added methods for the analysis of experiments with ordered treatments, including two parametric and nonparametric monotone analyses as well as approaches based on the robust general linear model and reversed ordinal logistic regression. Four groundbreaking chapters on single-case designs introduce powerful new analyses for simple and complex single-case experiments. This Second Edition also features coverage of advanced methods including: Simple and multiple analysis of covariance using both the Fisher approach and the general linear model approach Methods to manage assumption departures, including heterogeneous slopes, nonlinear functions, dichotomous dependent variables, and covariates affected by treatments Power analysis and the application of covariance analysis to randomized-block designs, two-factor designs, pre- and post-test designs, and multiple dependent variable designs Measurement error correction and propensity score methods developed for quasi-experiments, observational studies, and uncontrolled clinical trials Thoroughly updated to reflect the growing nature of the field, Analysis of Covariance and Alternatives is a suitable book for behavioral and medical scineces courses on design of experiments and regression and the upper-undergraduate and graduate levels. It also serves as an authoritative reference work for researchers and academics in the fields of medicine, clinical trials, epidemiology, public health, sociology, and engineering.
Book Synopsis Common Statistical Methods for Clinical Research with SAS Examples, Third Edition by : Glenn Walker
Download or read book Common Statistical Methods for Clinical Research with SAS Examples, Third Edition written by Glenn Walker and published by SAS Institute. This book was released on 2010-02-15 with total page 553 pages. Available in PDF, EPUB and Kindle. Book excerpt: Glenn Walker and Jack Shostak's Common Statistical Methods for Clinical Research with SAS Examples, Third Edition, is a thoroughly updated edition of the popular introductory statistics book for clinical researchers. This new edition has been extensively updated to include the use of ODS graphics in numerous examples as well as a new emphasis on PROC MIXED. Straightforward and easy to use as either a text or a reference, the book is full of practical examples from clinical research to illustrate both statistical and SAS methodology. Each example is worked out completely, step by step, from the raw data. Common Statistical Methods for Clinical Research with SAS Examples, Third Edition, is an applications book with minimal theory. Each section begins with an overview helpful to nonstatisticians and then drills down into details that will be valuable to statistical analysts and programmers. Further details, as well as bonus information and a guide to further reading, are presented in the extensive appendices. This text is a one-source guide for statisticians that documents the use of the tests used most often in clinical research, with assumptions, details, and some tricks--all in one place. This book is part of the SAS Press program.
Book Synopsis The Analysis of Case-control Studies by : Norman E. Breslow
Download or read book The Analysis of Case-control Studies written by Norman E. Breslow and published by . This book was released on 1980 with total page 352 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Applied Asymptotics by : A. R. Brazzale
Download or read book Applied Asymptotics written by A. R. Brazzale and published by Cambridge University Press. This book was released on 2007-05-31 with total page 256 pages. Available in PDF, EPUB and Kindle. Book excerpt: First practical treatment of small-sample asymptotics, enabling practitioners to apply new methods with confidence.
Book Synopsis Designing Social Inquiry by : Gary King
Download or read book Designing Social Inquiry written by Gary King and published by Princeton University Press. This book was released on 1994-05-22 with total page 259 pages. Available in PDF, EPUB and Kindle. Book excerpt: Designing Social Inquiry focuses on improving qualitative research, where numerical measurement is either impossible or undesirable. What are the right questions to ask? How should you define and make inferences about causal effects? How can you avoid bias? How many cases do you need, and how should they be selected? What are the consequences of unavoidable problems in qualitative research, such as measurement error, incomplete information, or omitted variables? What are proper ways to estimate and report the uncertainty of your conclusions?
Book Synopsis Case Studies in Bayesian Statistical Modelling and Analysis by : Clair L. Alston
Download or read book Case Studies in Bayesian Statistical Modelling and Analysis written by Clair L. Alston and published by John Wiley & Sons. This book was released on 2012-10-10 with total page 411 pages. Available in PDF, EPUB and Kindle. Book excerpt: Provides an accessible foundation to Bayesian analysis using real world models This book aims to present an introduction to Bayesian modelling and computation, by considering real case studies drawn from diverse fields spanning ecology, health, genetics and finance. Each chapter comprises a description of the problem, the corresponding model, the computational method, results and inferences as well as the issues that arise in the implementation of these approaches. Case Studies in Bayesian Statistical Modelling and Analysis: Illustrates how to do Bayesian analysis in a clear and concise manner using real-world problems. Each chapter focuses on a real-world problem and describes the way in which the problem may be analysed using Bayesian methods. Features approaches that can be used in a wide area of application, such as, health, the environment, genetics, information science, medicine, biology, industry and remote sensing. Case Studies in Bayesian Statistical Modelling and Analysis is aimed at statisticians, researchers and practitioners who have some expertise in statistical modelling and analysis, and some understanding of the basics of Bayesian statistics, but little experience in its application. Graduate students of statistics and biostatistics will also find this book beneficial.
