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Author: Victoria Cox Publisher: Apress ISBN: 1484222563 Category : Business & Economics Languages : en Pages : 334
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: Victoria Cox Publisher: Apress ISBN: 1484222563 Category : Business & Economics Languages : en Pages : 334
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: Cynthia Fraser Publisher: Springer ISBN: 3030203743 Category : Business & Economics Languages : en Pages : 419
Book Description
The revised Fifth Edition of this popular textbook is redesigned with Excel 2019 and the new inclusion of interactive, user-friendly JMP to encourage business students to develop competitive advantages for use in their future careers. Students learn to build models, produce statistics, and translate results into implications for decision makers. The text features new and updated examples and assignments, and each chapter discusses a focal case from the business world which can be analyzed using the statistical strategies and software provided in the text. Paralleling recent interest in climate change and sustainability, new case studies concentrate on issues such as the impact of drought on business, automobile emissions, and sustainable package goods. The book continues its coverage of inference, Monte Carlo simulation, contingency analysis, and linear and nonlinear regression. A new chapter is dedicated to conjoint analysis design and analysis, including complementary use of regression and JMP. For access to accompanying data sets, please email author Cynthia Fraser at [email protected].
Author: Cynthia Fraser Publisher: Springer ISBN: 3319321854 Category : Business & Economics Languages : en Pages : 482
Book Description
The revised Fourth Edition of this popular textbook is redesigned with Excel 2016 to encourage business students to develop competitive advantages for use in their future careers as decision makers. Students learn to build models using logic and experience, produce statistics using Excel 2016 with shortcuts, and translate results into implications for decision makers. The textbook features new examples and assignments on global markets, including cases featuring Chipotle and Costco. A number of examples focus on business in emerging global markets with particular emphasis on emerging markets in Latin America, China, and India. Results are linked to implications for decision making with sensitivity analyses to illustrate how alternate scenarios can be compared. The author emphasises communicating results effectively in plain English and with screenshots and compelling graphics in the form of memos and PowerPoints. Chapters include screenshots to make it easy to conduct analyses in Excel 2016. PivotTables and PivotCharts, used frequently in business, are introduced from the start. The Fourth Edition features Monte Carlo simulation in four chapters, as a tool to illustrate the range of possible outcomes from decision makers’ assumptions and underlying uncertainties. Model building with regression is presented as a process, adding levels of sophistication, with chapters on multicollinearity and remedies, forecasting and model validation, auto-correlation and remedies, indicator variables to represent segment differences, and seasonality, structural shifts or shocks in time series models. Special applications in market segmentation and portfolio analysis are offered, and an introduction to conjoint analysis is included. Nonlinear models are motivated with arguments of diminishing or increasing marginal response.
Author: Cynthia Fraser Publisher: Springer Science & Business Media ISBN: 144199856X Category : Business & Economics Languages : en Pages : 470
Book Description
In a revised and updated edition, this popular book shows readers how to build models using logic and experience, offers shortcuts for producing statistics using Excel 2010, and provides many real-world examples focused on business in emerging global markets.
Author: Zuzana Obertová Publisher: Academic Press ISBN: 0128157658 Category : Law Languages : en Pages : 434
Book Description
Statistics and Probability in Forensic Anthropology provides a practical guide for forensic scientists, primarily anthropologists and pathologists, on how to design studies, how to choose and apply statistical approaches, and how to interpret statistical outcomes in the forensic practice. As with other forensic, medical and biological disciplines, statistics have become increasingly important in forensic anthropology and legal medicine, but there is not a single book, which specifically addresses the needs of forensic anthropologists in relation to the research undertaken in the field and the interpretation of research outcomes and case findings within the setting of legal proceedings. The book includes the application of both frequentist and Bayesian statistics in relation to topics relevant for the research and the interpretation of findings in forensic anthropology, as well as general chapters on study design and statistical approaches addressing measurement errors and reliability. Scientific terminology understandable to students and advanced practitioners of forensic anthropology, pathology and related disciplines is used throughout. Additionally, Statistics and Probability in Forensic Anthropology facilitates sufficient understanding of the statistical procedures and data interpretation based on statistical outcomes and models, which helps the reader confidently present their work within the forensic context, either in the form of case reports for legal purposes or as research publications for the scientific community. - Contains the application of both frequentist and Bayesian statistics in relation to topics relevant for forensic anthropology research and the interpretation of findings - Provides examples of study designs and their statistical solutions, partly following the layout of scientific manuscripts on common topics in the field - Includes scientific terminology understandable to students and advanced practitioners of forensic anthropology, legal medicine and related disciplines
Author: Wang, John Publisher: IGI Global ISBN: 1799892212 Category : Computers Languages : en Pages : 3296
Book Description
Big data and machine learning are driving the Fourth Industrial Revolution. With the age of big data upon us, we risk drowning in a flood of digital data. Big data has now become a critical part of both the business world and daily life, as the synthesis and synergy of machine learning and big data has enormous potential. Big data and machine learning are projected to not only maximize citizen wealth, but also promote societal health. As big data continues to evolve and the demand for professionals in the field increases, access to the most current information about the concepts, issues, trends, and technologies in this interdisciplinary area is needed. The Encyclopedia of Data Science and Machine Learning examines current, state-of-the-art research in the areas of data science, machine learning, data mining, and more. It provides an international forum for experts within these fields to advance the knowledge and practice in all facets of big data and machine learning, emphasizing emerging theories, principals, models, processes, and applications to inspire and circulate innovative findings into research, business, and communities. Covering topics such as benefit management, recommendation system analysis, and global software development, this expansive reference provides a dynamic resource for data scientists, data analysts, computer scientists, technical managers, corporate executives, students and educators of higher education, government officials, researchers, and academicians.
Author: Kunal Pal Publisher: Academic Press ISBN: 0323859542 Category : Technology & Engineering Languages : en Pages : 434
Book Description
Advanced Methods in Biomedical Signal Processing and Analysis presents state-of-the-art methods in biosignal processing, including recurrence quantification analysis, heart rate variability, analysis of the RRI time-series signals, joint time-frequency analyses, wavelet transforms and wavelet packet decomposition, empirical mode decomposition, modeling of biosignals, Gabor Transform, empirical mode decomposition. The book also gives an understanding of feature extraction, feature ranking, and feature selection methods, while also demonstrating how to apply artificial intelligence and machine learning to biosignal techniques. - Gives advanced methods in signal processing - Includes machine and deep learning methods - Presents experimental case studies
Author: Amoroso, R. Publisher: Food & Agriculture Org. [Author] ISBN: 9251387095 Category : Technology & Engineering Languages : en Pages : 124
Book Description
In fisheries science and management, it is not uncommon that fishery data are used at “face value”, as inputs into data-limited assessments or empirical indicator-based frameworks for management, without first conducting a thorough exploration and critical review of the data. [Author] This practice may lead to biases in results and misdirected fishery management actions. [Author] To address intermediate steps between data collection and any analysis used to inform stock status, this manual provides guidance on how to prepare, explore and critically review fishery data in data-limited situations. [Author] Throughout the manual, guidance and sample data are provided primarily in Microsoft Excel or in comma separated value (CSV) file formats, as well as through FishualizeR, a publicly available, web-based, R Shiny app that was developed to support the manual. [Author] Instructions in this manual are not intended to present a single, prescriptive path, but rather to provide guidance that may be further tailored to each individual context. [Author] It is the authors’ hope and intent that the guidance contained in this manual will allow users to better understand their data, make corrections, and gain a deeper understanding of the data’s utility in assessment and management of data-limited fisheries. [Author]
Author: Juan F. de Paz Santana Publisher: Springer Nature ISBN: 303087687X Category : Technology & Engineering Languages : en Pages : 406
Book Description
This book includes recent research on disruptive technologies, tech ethics, and artificial intelligence. Due to the important advances in technologies such as artificial intelligence, big data, the Internet of Things or bioinformatics produced in recent years, it is necessary to conduct a thorough review of current ethical patterns. One of the research fields that is in full expansion and with a broad future is technology ethics or tech ethics. Just a few years ago, this type of research was a small part, and they did not have too many technology researchers involved. At present, due to the explosion of new applications of artificial intelligence, their problems and their legal barriers have flourished innumerable initiatives, declarations, principles, guides and analyses focused on measuring the social impact of these systems and on the development of a more ethical technology. It is, therefore, a problem that needs to be addressed from an academic and multidisciplinary point of view, where experts in ethics and behavior work together with experts in new and disruptive technologies. The international conference “Disruptive Technologies Tech Ethics and Artificial Intelligence” (DITTET 2021) provides a forum to present and discuss the latest scientific and technical advances and their implications in the field of ethics. It also provides a forum for experts to present their latest research in disruptive technologies, promoting knowledge transfer. It provides a unique opportunity to bring together experts in different fields, academics and professionals to exchange their experience in the development and deployment of disruptive technologies, artificial intelligence and their ethical problems. DiTTEt intends to bring together researchers and developers from industry, humanities and academia to report on the latest scientific advances and the application of artificial intelligence as well as its ethical implications in fields as diverse as climate change, politics, economy or security in today’s world. This book constitutes the refereed proceedings selected by an expert panel through a peer-review process. All these works will be presented by the experts in the different sessions organized at the DITTET congress to be held at the Pontifical University of Salamanca (Salamanca, Spain) on September 15, 26 and 17, 2021.
Author: Álvaro Rocha Publisher: Springer Nature ISBN: 9811641269 Category : Technology & Engineering Languages : en Pages : 765
Book Description
This book gathers high-quality papers presented at International Conference on Science, Technology and Innovation for Society (CITIS 2021), held in Guayaquil, Ecuador, on May 26–28, 2021. This book will present the recent research trends in the fields of software engineering, big data analysis, cloud computing, data engineering, data management and data mining, machine learning, deep learning, artificial intelligence, smart systems, robotics and automation, mechatronic design, and industrial processes design.
Author: Victoria Cox
Author: Victoria Cox
Author: Cynthia Fraser
Author: Cynthia Fraser
Author: Cynthia Fraser
Author: Zuzana Obertová
Author: Wang, John
Author: Kunal Pal
Author: Amoroso, R.
Author: Juan F. de Paz Santana
Author: Álvaro Rocha