Download or read book Statistical Thinking written by Roger W. Hoerl and published by John Wiley & Sons. This book was released on 2012-04-09 with total page 544 pages. Available in PDF, EPUB and Kindle. Book excerpt: How statistical thinking and methodology can help you make crucial business decisions Straightforward 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 helpful Provides case studies that illustrate how to integrate several statistical tools into the decision-making process Facilitates and encourages an experiential learning environment to enable you to apply material to actual problems With 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.
Download or read book Statistical Thinking for Managers written by J.A. John and published by CRC Press. This book was released on 2001-06-28 with total page 356 pages. Available in PDF, EPUB and Kindle. Book excerpt: All business activities are subject to variability. As a consequence, managers and business students need the ability to think statistically about how to deal with the resulting uncertainty and its effect on decision-making in management and commerce. To give them that ability, there is a growing recognition that we must change the way business statistics is taught. Traditional texts tend to focus on probability, mathematical detail, and heavy computation, and thus fail to meet the real needs of future business managers. Statistical Thinking for Managers takes a very different, very practical, approach that presents even sophisticated statistics concepts with a minimum of mathematics. It focuses on statistical thinking and discusses a range of topics that specifically apply to managers in business. Its scenario-based, interactive format and integrated use of Excel facilitate and reinforce the learning experience. Through this innovative treatment, readers will gain the ability to: " Appreciate basic statistical ideas " Use a scientific approach to problem solving " Understand the nature of variability " Use meaningful information to make informed decisions " Think in terms of processes and systems and develop strategies for process improvement Designed as an introductory text in business statistics, Statistical Thinking for Managers challenges the way students look at business problems and issues. It shows them the importance of statistics in all aspects of business and equips them with the skills they need to make informed and effective decisions.
Download or read book Statistical Thinking in Business written by J. A. John and published by CRC Press. This book was released on 2005-08-29 with total page 408 pages. Available in PDF, EPUB and Kindle. Book excerpt: Business 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
Download or read book Improving Performance Through Statistical Thinking written by Galen C. Britz and published by . This book was released on 2000 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume presents a clear and practical explanation of statistical thinking without the typical equations and formulas. It aims to bridge the gap from concept to application by providing step-by-step guidance on how to get started on problems.
Download or read book Statistical Thinking for Non Statisticians in Drug Regulation written by Richard Kay and published by John Wiley & Sons. This book was released on 2014-10-23 with total page 370 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistical Thinking for Non-Statisticians in Drug Regulation, Second Edition, is a need-to-know guide to understanding statistical methodology, statistical data and results within drug development and clinical trials. It provides non-statisticians working in the pharmaceutical and medical device industries with an accessible introduction to the knowledge they need when working with statistical information and communicating with statisticians. It covers the statistical aspects of design, conduct, analysis and presentation of data from clinical trials in drug regulation and improves the ability to read, understand and critically appraise statistical methodology in papers and reports. As such, it is directly concerned with the day-to-day practice and the regulatory requirements of drug development and clinical trials. Fully conversant with current regulatory requirements, this second edition includes five new chapters covering Bayesian statistics, adaptive designs, observational studies, methods for safety analysis and monitoring and statistics for diagnosis. Authored by a respected lecturer and consultant to the pharmaceutical industry, Statistical Thinking for Non-Statisticians in Drug Regulation is an ideal guide for physicians, clinical research scientists, managers and associates, data managers, medical writers, regulatory personnel and for all non-statisticians working and learning within the pharmaceutical industry.
Download or read book Regression Modeling Strategies written by Frank E. Harrell and published by Springer Science & Business Media. This book was released on 2013-03-09 with total page 583 pages. Available in PDF, EPUB and Kindle. Book excerpt: Many texts are excellent sources of knowledge about individual statistical tools, but the art of data analysis is about choosing and using multiple tools. Instead of presenting isolated techniques, this text emphasizes problem solving strategies that address the many issues arising when developing multivariable models using real data and not standard textbook examples. It includes imputation methods for dealing with missing data effectively, methods for dealing with nonlinear relationships and for making the estimation of transformations a formal part of the modeling process, methods for dealing with "too many variables to analyze and not enough observations," and powerful model validation techniques based on the bootstrap. This text realistically deals with model uncertainty and its effects on inference to achieve "safe data mining".
Download or read book Statistical Thinking for Managers written by David K. Hildebrand and published by Brooks/Cole. This book was released on 1991 with total page 1128 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Statistical Thinking Through Media Examples written by Anthony Donoghue and published by Cognella Academic Publishing. This book was released on 2021-08-02 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
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
Download or read book Statistical Thinking for Managers written by David K. Hildebrand and published by South-Western College. This book was released on 1998 with total page 876 pages. Available in PDF, EPUB and Kindle. Book excerpt: Focusing on the analysis of data using modern statistical and spreadsheet software, Hildebrand and Ott emphasize making sense of data and discuss not only how a statistical method is applied, but why and why not. Throughout the book, the authors integrate computer use into the development of statistical concepts, emphasizing the value of looking at data to make sure the right questions are being asked. The real-life applications and examples throughout challenge students to think like managers. The case that concludes every chapter asks students to deal with a relatively unstructured situation and to explain the statistical reasoning in nontechnical language. Modern statistical methods, including resampling and bootstrapping are included. In addition, the authors emphasize quality control and improvement throughout the book and include three full chapters on regression and correlation methods.
Download or read book The Challenge of Developing Statistical Literacy Reasoning and Thinking written by Dani Ben-Zvi and published by Springer Science & Business Media. This book was released on 2006-02-23 with total page 423 pages. Available in PDF, EPUB and Kindle. Book excerpt: Unique in that it collects, presents, and synthesizes cutting edge research on different aspects of statistical reasoning and applies this research to the teaching of statistics to students at all educational levels, this volume will prove of great value to mathematics and statistics education researchers, statistics educators, statisticians, cognitive psychologists, mathematics teachers, mathematics and statistics curriculum developers, and quantitative literacy experts in education and government.
Download or read book Fundamental Statistical Principles for the Neurobiologist written by Stephen W. Scheff and published by Academic Press. This book was released on 2016-02-11 with total page 236 pages. Available in PDF, EPUB and Kindle. Book excerpt: Fundamental Statistical Principles for Neurobiologists introduces readers to basic experimental design and statistical thinking in a comprehensive, relevant manner. This book is an introductory statistics book that covers fundamental principles written by a neuroscientist who understands the plight of the neuroscience graduate student and the senior investigator. It summarizes the fundamental concepts associated with statistical analysis that are useful for the neuroscientist, and provides understanding of a particular test in language that is more understandable to this specific audience, with the overall purpose of explaining which statistical technique should be used in which situation. Different types of data are discussed such as how to formulate a research hypothesis, the primary types of statistical errors and statistical power, followed by how to actually graph data and what kinds of mistakes to avoid. Chapters discuss variance, standard deviation, standard error, mean, confidence intervals, correlation, regression, parametric vs. nonparametric statistical tests, ANOVA, and post hoc analyses. Finally, there is a discussion on how to deal with data points that appear to be "outliers" and what to do when there is missing data, an issue that has not sufficiently been covered in literature. - An introductory guide to statistics aimed specifically at the neuroscience audience - Contains numerous examples with actual data that is used in the analysis - Gives the investigators a starting pointing for evaluating data in easy-to-understand language - Explains in detail many different statistical tests commonly used by neuroscientists
Download or read book An Introduction to Statistical Analysis for Business and Industry written by Michael Stuart and published by Wiley. This book was released on 2010-07-13 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is an introductory statistics textbook for business and management students which uses the innovative approach of 'statistical thinking'. Statistics courses are essential for business students but traditional teaching methods are often seen as difficult and are therefore unpopular; this book aims to offer a new and more appealing way of learning to this market. 'An Introduction to Statistical Analysis for Business and Industry' presents a new and innovative introduction to statistics which trains students directly to address problems which commonly arise in business and industry. Having read and worked through the book and its accompanying manual, students should have the essential skills necessary to apply statistical thinking in business and be able to: –recognise statistical variation in processes, –apply a statistical problem-solving strategy for process improvement, –select and apply appropriate methods of statistical analysis.
Download or read book The Basic Practice of Statistics written by David S. Moore and published by Palgrave Macmillan. This book was released on 2010 with total page 975 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is a clear and innovative overview of statistics which emphasises major ideas, essential skills and real-life data. The organisation and design has been improved for the fifth edition, coverage of engaging, real-world topics has been increased and content has been updated to appeal to today's trends and research.
Download or read book Principles of Managerial Statistics and Data Science written by Roberto Rivera and published by John Wiley & Sons. This book was released on 2020-02-05 with total page 688 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introduces readers to the principles of managerial statistics and data science, with an emphasis on statistical literacy of business students Through a statistical perspective, this book introduces readers to the topic of data science, including Big Data, data analytics, and data wrangling. Chapters include multiple examples showing the application of the theoretical aspects presented. It features practice problems designed to ensure that readers understand the concepts and can apply them using real data. Over 100 open data sets used for examples and problems come from regions throughout the world, allowing the instructor to adapt the application to local data with which students can identify. Applications with these data sets include: Assessing if searches during a police stop in San Diego are dependent on driver’s race Visualizing the association between fat percentage and moisture percentage in Canadian cheese Modeling taxi fares in Chicago using data from millions of rides Analyzing mean sales per unit of legal marijuana products in Washington state Topics covered in Principles of Managerial Statistics and Data Science include:data visualization; descriptive measures; probability; probability distributions; mathematical expectation; confidence intervals; and hypothesis testing. Analysis of variance; simple linear regression; and multiple linear regression are also included. In addition, the book offers contingency tables, Chi-square tests, non-parametric methods, and time series methods. The textbook: Includes academic material usually covered in introductory Statistics courses, but with a data science twist, and less emphasis in the theory Relies on Minitab to present how to perform tasks with a computer Presents and motivates use of data that comes from open portals Focuses on developing an intuition on how the procedures work Exposes readers to the potential in Big Data and current failures of its use Supplementary material includes: a companion website that houses PowerPoint slides; an Instructor's Manual with tips, a syllabus model, and project ideas; R code to reproduce examples and case studies; and information about the open portal data Features an appendix with solutions to some practice problems Principles of Managerial Statistics and Data Science is a textbook for undergraduate and graduate students taking managerial Statistics courses, and a reference book for working business professionals.
Download or read book Thinking Fast and Slow written by Daniel Kahneman and published by Farrar, Straus and Giroux. This book was released on 2011-10-25 with total page 511 pages. Available in PDF, EPUB and Kindle. Book excerpt: *Major New York Times Bestseller *More than 2.6 million copies sold *One of The New York Times Book Review's ten best books of the year *Selected by The Wall Street Journal as one of the best nonfiction books of the year *Presidential Medal of Freedom Recipient *Daniel Kahneman's work with Amos Tversky is the subject of Michael Lewis's best-selling The Undoing Project: A Friendship That Changed Our Minds In his mega bestseller, Thinking, Fast and Slow, Daniel Kahneman, world-famous psychologist and winner of the Nobel Prize in Economics, takes us on a groundbreaking tour of the mind and explains the two systems that drive the way we think. System 1 is fast, intuitive, and emotional; System 2 is slower, more deliberative, and more logical. The impact of overconfidence on corporate strategies, the difficulties of predicting what will make us happy in the future, the profound effect of cognitive biases on everything from playing the stock market to planning our next vacation—each of these can be understood only by knowing how the two systems shape our judgments and decisions. Engaging the reader in a lively conversation about how we think, Kahneman reveals where we can and cannot trust our intuitions and how we can tap into the benefits of slow thinking. He offers practical and enlightening insights into how choices are made in both our business and our personal lives—and how we can use different techniques to guard against the mental glitches that often get us into trouble. Topping bestseller lists for almost ten years, Thinking, Fast and Slow is a contemporary classic, an essential book that has changed the lives of millions of readers.
Download or read book Statistical Inference as Severe Testing written by Deborah G. Mayo and published by Cambridge University Press. This book was released on 2018-09-20 with total page 503 pages. Available in PDF, EPUB and Kindle. Book excerpt: Mounting failures of replication in social and biological sciences give a new urgency to critically appraising proposed reforms. This book pulls back the cover on disagreements between experts charged with restoring integrity to science. It denies two pervasive views of the role of probability in inference: to assign degrees of belief, and to control error rates in a long run. If statistical consumers are unaware of assumptions behind rival evidence reforms, they can't scrutinize the consequences that affect them (in personalized medicine, psychology, etc.). The book sets sail with a simple tool: if little has been done to rule out flaws in inferring a claim, then it has not passed a severe test. Many methods advocated by data experts do not stand up to severe scrutiny and are in tension with successful strategies for blocking or accounting for cherry picking and selective reporting. Through a series of excursions and exhibits, the philosophy and history of inductive inference come alive. Philosophical tools are put to work to solve problems about science and pseudoscience, induction and falsification.
