Statistics For Making Decisions
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Statistics For Making Decisions
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Author : Nicholas T. Longford
language : en
Publisher: CRC Press
Release Date : 2021-03-30
Statistics For Making Decisions written by Nicholas T. Longford and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-03-30 with Mathematics categories.
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.
Translating Statistics To Make Decisions
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Author : Victoria Cox
language : en
Publisher: Apress
Release Date : 2017-03-10
Translating Statistics To Make Decisions written by Victoria Cox and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-03-10 with Business & Economics categories.
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 walksreaders 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
Data Science For Business And Decision Making
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Author : Luiz Paulo Favero
language : en
Publisher: Academic Press
Release Date : 2019-04-11
Data Science For Business And Decision Making written by Luiz Paulo Favero and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-04-11 with Business & Economics categories.
Data Science for Business and Decision Making covers both statistics and operations research while most competing textbooks focus on one or the other. As a result, the book more clearly defines the principles of business analytics for those who want to apply quantitative methods in their work. Its emphasis reflects the importance of regression, optimization and simulation for practitioners of business analytics. Each chapter uses a didactic format that is followed by exercises and answers. Freely-accessible datasets enable students and professionals to work with Excel, Stata Statistical Software®, and IBM SPSS Statistics Software®. - Combines statistics and operations research modeling to teach the principles of business analytics - Written for students who want to apply statistics, optimization and multivariate modeling to gain competitive advantages in business - Shows how powerful software packages, such as SPSS and Stata, can create graphical and numerical outputs
Asymptotic Methods In Statistical Decision Theory
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Author : Lucien Le Cam
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Asymptotic Methods In Statistical Decision Theory written by Lucien Le Cam and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Mathematics categories.
This book grew out of lectures delivered at the University of California, Berkeley, over many years. The subject is a part of asymptotics in statistics, organized around a few central ideas. The presentation proceeds from the general to the particular since this seemed the best way to emphasize the basic concepts. The reader is expected to have been exposed to statistical thinking and methodology, as expounded for instance in the book by H. Cramer [1946] or the more recent text by P. Bickel and K. Doksum [1977]. Another pos sibility, closer to the present in spirit, is Ferguson [1967]. Otherwise the reader is expected to possess some mathematical maturity, but not really a great deal of detailed mathematical knowledge. Very few mathematical objects are used; their assumed properties are simple; the results are almost always immediate consequences of the definitions. Some objects, such as vector lattices, may not have been included in the standard background of a student of statistics. For these we have provided a summary of relevant facts in the Appendix. The basic structures in the whole affair are systems that Blackwell called "experiments" and "transitions" between them. An "experiment" is a mathe matical abstraction intended to describe the basic features of an observational process if that process is contemplated in advance of its implementation. Typically, an experiment consists of a set E> of theories about what may happen in the observational process.
Basic Statistics With R
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Author : Stephen C. Loftus
language : en
Publisher: Academic Press
Release Date : 2021-02-20
Basic Statistics With R written by Stephen C. Loftus and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-02-20 with Mathematics categories.
Basic Statistics with R: Reaching Decisions with Data provides an understanding of the processes at work in using data for results. Sections cover data collection and discuss exploratory analyses, including visual graphs, numerical summaries, and relationships between variables - basic probability, and statistical inference - including hypothesis testing and confidence intervals. All topics are taught using real-data drawn from various fields, including economics, biology, political science and sports. Using this wide variety of motivating examples allows students to directly connect and make statistics essential to their field of interest, rather than seeing it as a separate and ancillary knowledge area. In addition to introducing students to statistical topics using real data, the book provides a gentle introduction to coding, having the students use the statistical language and software R. Students learn to load data, calculate summary statistics, create graphs and do statistical inference using R with either Windows or Macintosh machines. - Features real-data to give students an engaging practice to connect with their areas of interest - Evolves from basic problems that can be worked by hand to the elementary use of opensource R software - Offers a direct, clear approach highlighted by useful visuals and examples
Mathematical Statistics With Applications
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Author : Kandethody M. Ramachandran
language : en
Publisher: Academic Press
Release Date : 2009-03-13
Mathematical Statistics With Applications written by Kandethody M. Ramachandran and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-03-13 with Mathematics categories.
Mathematical Statistics with Applications provides a calculus-based theoretical introduction to mathematical statistics while emphasizing interdisciplinary applications as well as exposure to modern statistical computational and simulation concepts that are not covered in other textbooks. Includes the Jackknife, Bootstrap methods, the EM algorithms and Markov chain Monte Carlo methods. Prior probability or statistics knowledge is not required. Step-by-step procedure to solve real problems, making the topic more accessible Exercises blend theory and modern applications Practical, real-world chapter projects Provides an optional section in each chapter on using Minitab, SPSS and SAS commands
The Paradox Of Choice
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Author : Barry Schwartz
language : en
Publisher: Harper Collins
Release Date : 2009-10-13
The Paradox Of Choice written by Barry Schwartz and has been published by Harper Collins this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-10-13 with Psychology categories.
Whether we're buying a pair of jeans, ordering a cup of coffee, selecting a long-distance carrier, applying to college, choosing a doctor, or setting up a 401(k), everyday decisions—both big and small—have become increasingly complex due to the overwhelming abundance of choice with which we are presented. As Americans, we assume that more choice means better options and greater satisfaction. But beware of excessive choice: choice overload can make you question the decisions you make before you even make them, it can set you up for unrealistically high expectations, and it can make you blame yourself for any and all failures. In the long run, this can lead to decision-making paralysis, anxiety, and perpetual stress. And, in a culture that tells us that there is no excuse for falling short of perfection when your options are limitless, too much choice can lead to clinical depression. In The Paradox of Choice, Barry Schwartz explains at what point choice—the hallmark of individual freedom and self-determination that we so cherish—becomes detrimental to our psychological and emotional well-being. In accessible, engaging, and anecdotal prose, Schwartz shows how the dramatic explosion in choice—from the mundane to the profound challenges of balancing career, family, and individual needs—has paradoxically become a problem instead of a solution. Schwartz also shows how our obsession with choice encourages us to seek that which makes us feel worse. By synthesizing current research in the social sciences, Schwartz makes the counter intuitive case that eliminating choices can greatly reduce the stress, anxiety, and busyness of our lives. He offers eleven practical steps on how to limit choices to a manageable number, have the discipline to focus on those that are important and ignore the rest, and ultimately derive greater satisfaction from the choices you have to make.
Getting Started With Business Analytics
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Author : David Roi Hardoon
language : en
Publisher: CRC Press
Release Date : 2013-03-26
Getting Started With Business Analytics written by David Roi Hardoon and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-03-26 with Business & Economics categories.
Assuming no prior knowledge or technical skills, Getting Started with Business Analytics: Insightful Decision-Making explores the contents, capabilities, and applications of business analytics. It bridges the worlds of business and statistics and describes business analytics from a non-commercial standpoint. The authors demystify the main concepts
Introduction To Statistical Decision Theory
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Author : Silvia Bacci
language : en
Publisher: CRC Press
Release Date : 2019-07-11
Introduction To Statistical Decision Theory written by Silvia Bacci and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-07-11 with Mathematics categories.
Introduction to Statistical Decision Theory: Utility Theory and Causal Analysis provides the theoretical background to approach decision theory from a statistical perspective. It covers both traditional approaches, in terms of value theory and expected utility theory, and recent developments, in terms of causal inference. The book is specifically designed to appeal to students and researchers that intend to acquire a knowledge of statistical science based on decision theory. Features Covers approaches for making decisions under certainty, risk, and uncertainty Illustrates expected utility theory and its extensions Describes approaches to elicit the utility function Reviews classical and Bayesian approaches to statistical inference based on decision theory Discusses the role of causal analysis in statistical decision theory
Statistical Methods In Decision Science
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Author : Pasquale De Marco
language : en
Publisher: Pasquale De Marco
Release Date : 2025-07-27
Statistical Methods In Decision Science written by Pasquale De Marco and has been published by Pasquale De Marco this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-07-27 with Business & Economics categories.
**Statistical Methods in Decision Science** provides a comprehensive overview of the statistical methods used in decision science, covering both foundational concepts and advanced techniques. Written in a clear and accessible style, this book is designed for an American audience and suitable for a wide range of readers, including students, researchers, and practitioners in decision science, statistics, and related fields. The book begins with an introduction to statistical decision science, discussing its importance and applications in various fields. It then covers descriptive statistics, which provide a summary of data, and inferential statistics, which allow us to make inferences about a population based on a sample. The book also covers more advanced topics such as Bayesian statistics, decision theory, risk analysis, data mining, and machine learning. These techniques provide powerful tools for making decisions under uncertainty, and have a wide range of applications in fields such as finance, healthcare, marketing, environmental science, and public policy. Each chapter includes detailed explanations of the concepts and techniques covered, along with real-world examples and case studies to illustrate their application. The book also includes exercises and discussion questions to help readers test their understanding of the material. Overall, this book is an essential resource for anyone interested in learning about statistical methods used in decision science. It provides a comprehensive overview of the field, from foundational concepts to advanced techniques, and is written in a clear and accessible style. Whether you are a student looking to gain a solid foundation in statistical decision science or a practitioner seeking to enhance your knowledge and skills, this book has something to offer you. With its clear explanations, real-world examples, and exercises, this book will help you to develop the skills and knowledge you need to make informed decisions under uncertainty. If you like this book, write a review!