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Author: Nicholas T. Longford
Publisher: CRC Press
ISBN: 1000347583
Category : Mathematics
Languages : en
Pages : 309
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Book Description
A constructive response to the criticisms of using hypothesis testing for making decisions Integrating the context (the client’s perspective, value judgments, priorities and remits) in the analysis, combining it with sensitivity analysis that handles the uncertainty arising in elicitation of the context Treatment of the problems by elementary (analytical) methods Applications that illustrate the methods in their best light • Drawing on several publications in high-profile journals in applied statistics
Author: Nicholas T. Longford
Publisher: CRC Press
ISBN: 1000347583
Category : Mathematics
Languages : en
Pages : 309
Get Book
Book Description
A constructive response to the criticisms of using hypothesis testing for making decisions Integrating the context (the client’s perspective, value judgments, priorities and remits) in the analysis, combining it with sensitivity analysis that handles the uncertainty arising in elicitation of the context Treatment of the problems by elementary (analytical) methods Applications that illustrate the methods in their best light • Drawing on several publications in high-profile journals in applied statistics
Author: Morris Hamburg
Publisher: Houghton Mifflin Harcourt P
ISBN:
Category : Mathematics
Languages : en
Pages : 872
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Book Description
Author: John C. G. Boot
Publisher:
ISBN:
Category : Decision making
Languages : en
Pages : 674
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Book Description
Textbook on statistical methods used in solving problems prior to decision making in management - covers problems of sampling, estimation, hypothesis testing, regression and correlation, forecasting, statistical methods for quality control, etc., and includes an appendix on the use of computers in statistical analysis. Bibliography pp. 627 to 631.
Author: Nicholas T. Longford
Publisher: CRC Press
ISBN: 1000347605
Category : Mathematics
Languages : en
Pages : 273
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Book Description
Making decisions is a ubiquitous mental activity in our private and professional or public lives. It entails choosing one course of action from an available shortlist of options. Statistics for Making Decisions places decision making at the centre of statistical inference, proposing its theory as a new paradigm for statistical practice. The analysis in this paradigm is earnest about prior information and the consequences of the various kinds of errors that may be committed. Its conclusion is a course of action tailored to the perspective of the specific client or sponsor of the analysis. The author’s intention is a wholesale replacement of hypothesis testing, indicting it with the argument that it has no means of incorporating the consequences of errors which self-evidently matter to the client. The volume appeals to the analyst who deals with the simplest statistical problems of comparing two samples (which one has a greater mean or variance), or deciding whether a parameter is positive or negative. It combines highlighting the deficiencies of hypothesis testing with promoting a principled solution based on the idea of a currency for error, of which we want to spend as little as possible. This is implemented by selecting the option for which the expected loss is smallest (the Bayes rule). The price to pay is the need for a more detailed description of the options, and eliciting and quantifying the consequences (ramifications) of the errors. This is what our clients do informally and often inexpertly after receiving outputs of the analysis in an established format, such as the verdict of a hypothesis test or an estimate and its standard error. As a scientific discipline and profession, statistics has a potential to do this much better and deliver to the client a more complete and more relevant product. Nicholas T. Longford is a senior statistician at Imperial College, London, specialising in statistical methods for neonatal medicine. His interests include causal analysis of observational studies, decision theory, and the contest of modelling and design in data analysis. His longer-term appointments in the past include Educational Testing Service, Princeton, NJ, USA, de Montfort University, Leicester, England, and directorship of SNTL, a statistics research and consulting company. He is the author of over 100 journal articles and six other monographs on a variety of topics in applied statistics.
Author: Victoria Cox
Publisher: Apress
ISBN: 1484222563
Category : Business & Economics
Languages : en
Pages : 334
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Book Description
Examine and solve the common misconceptions and fallacies that non-statisticians bring to their interpretation of statistical results. Explore the many pitfalls that non-statisticians—and also statisticians who present statistical reports to non-statisticians—must avoid if statistical results are to be correctly used for evidence-based business decision making. Victoria Cox, senior statistician at the United Kingdom’s Defence Science and Technology Laboratory (Dstl), distills the lessons of her long experience presenting the actionable results of complex statistical studies to users of widely varying statistical sophistication across many disciplines: from scientists, engineers, analysts, and information technologists to executives, military personnel, project managers, and officials across UK government departments, industry, academia, and international partners. The author shows how faulty statistical reasoning often undermines the utility of statistical results even among those with advanced technical training. Translating Statistics teaches statistically naive readers enough about statistical questions, methods, models, assumptions, and statements that they will be able to extract the practical message from statistical reports and better constrain what conclusions cannot be made from the results. To non-statisticians with some statistical training, this book offers brush-ups, reminders, and tips for the proper use of statistics and solutions to common errors. To fellow statisticians, the author demonstrates how to present statistical output to non-statisticians to ensure that the statistical results are correctly understood and properly applied to real-world tasks and decisions. The book avoids algebra and proofs, but it does supply code written in R for those readers who are motivated to work out examples. Pointing along the way to instructive examples of statistics gone awry, Translating Statistics walks readers through the typical course of a statistical study, progressing from the experimental design stage through the data collection process, exploratory data analysis, descriptive statistics, uncertainty, hypothesis testing, statistical modelling and multivariate methods, to graphs suitable for final presentation. The steady focus throughout the book is on how to turn the mathematical artefacts and specialist jargon that are second nature to statisticians into plain English for corporate customers and stakeholders. The final chapter neatly summarizes the book’s lessons and insights for accurately communicating statistical reports to the non-statisticians who commission and act on them. What You'll Learn Recognize and avoid common errors and misconceptions that cause statistical studies to be misinterpreted and misused by non-statisticians in organizational settings Gain a practical understanding of the methods, processes, capabilities, and caveats of statistical studies to improve the application of statistical data to business decisions See how to code statistical solutions in R Who This Book Is For Non-statisticians—including both those with and without an introductory statistics course under their belts—who consume statistical reports in organizational settings, and statisticians who seek guidance for reporting statistical studies to non-statisticians in ways that will be accurately understood and will inform sound business and technical decisions
Author: David F. Groebner
Publisher: Prentice Hall
ISBN:
Category : Business & Economics
Languages : en
Pages : 1080
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Book Description
This comprehensive, user-friendly reference explores many descriptive and inferential statistical topics integral to business problem solving and decision making. Chapter topics include data collection; graphs, charts, and tables; probability distributions; sampling distributions; estimating population values; hypothesis testing; quality management and statistical process control; linear regression and correlation analysis; model building and multiple regression analysis; and nonparametric statistics. For business professionals involved in data presentations and descriptive analyses.
Author: David Tanner
Publisher: SAGE
ISBN: 1412969778
Category : Education
Languages : en
Pages : 553
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Book Description
Government scrutiny and intensified oversight have dramatically changed the landscape of education in recent years. Observers want to know how schools compare, which district is best, which states are spending the most per student on education, whether reforms are making a difference, and why so many students are failing. Some of these questions require technical answers that educators historically redirected to outside experts, but the questions leveled at all educators have become so acute and persistent that they can no longer be outsourced. This text helps educators develop the tools and the conceptual understanding needed to provide definitive answers to difficult statistical questions facing education today.
Author: John Winsor Pratt
Publisher: MIT Press
ISBN: 9780262161442
Category : Business & Economics
Languages : en
Pages : 906
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Book Description
They then examine the Bernoulli, Poisson, and Normal (univariate and multivariate) data generating processes.
Author: David W. Blakeslee
Publisher:
ISBN: 9780395430446
Category : Business & Economics
Languages : en
Pages : 380
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Book Description
Author: Ya-lun Chou
Publisher:
ISBN:
Category : Business & Economics
Languages : en
Pages : 648
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Book Description
