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Author: Shelemyahu Zacks
Publisher: Springer Nature
ISBN: 3030394344
Category : Mathematics
Languages : en
Pages : 217
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Book Description
This monograph highlights the connection between the theoretical work done by research statisticians and the impact that work has on various industries. Drawing on decades of experience as an industry consultant, the author details how his contributions have had a lasting impact on the field of statistics as a whole. Aspiring statisticians and data scientists will be motivated to find practical applications for their knowledge, as they see how such work can yield breakthroughs in their field. Each chapter highlights a consulting position the author held that resulted in a significant contribution to statistical theory. Topics covered include tracking processes with change points, estimating common parameters, crossing fields with absorption points, military operations research, sampling surveys, stochastic visibility in random fields, reliability analysis, applied probability, and more. Notable advancements within each of these topics are presented by analyzing the problems facing various industries, and how solving those problems contributed to the development of the field. The Career of a Research Statistician is ideal for researchers, graduate students, or industry professionals working in statistics. It will be particularly useful for up-and-coming statisticians interested in the promising connection between academia and industry.
Author: Shelemyahu Zacks
Publisher: Springer Nature
ISBN: 3030394344
Category : Mathematics
Languages : en
Pages : 217
Get Book
Book Description
This monograph highlights the connection between the theoretical work done by research statisticians and the impact that work has on various industries. Drawing on decades of experience as an industry consultant, the author details how his contributions have had a lasting impact on the field of statistics as a whole. Aspiring statisticians and data scientists will be motivated to find practical applications for their knowledge, as they see how such work can yield breakthroughs in their field. Each chapter highlights a consulting position the author held that resulted in a significant contribution to statistical theory. Topics covered include tracking processes with change points, estimating common parameters, crossing fields with absorption points, military operations research, sampling surveys, stochastic visibility in random fields, reliability analysis, applied probability, and more. Notable advancements within each of these topics are presented by analyzing the problems facing various industries, and how solving those problems contributed to the development of the field. The Career of a Research Statistician is ideal for researchers, graduate students, or industry professionals working in statistics. It will be particularly useful for up-and-coming statisticians interested in the promising connection between academia and industry.
Author: Gerald J. Hahn
Publisher: John Wiley & Sons
ISBN: 1118490134
Category : Mathematics
Languages : en
Pages : 358
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Book Description
A valuable guide to a successful career as a statistician A Career in Statistics: Beyond the Numbers prepares readers for careers in statistics by emphasizing essential concepts and practices beyond the technical tools provided in standard courses and texts. This insider's guide from internationally recognized applied statisticians helps readers decide whether a career in statistics is right for them, provides hands-on guidance on how to prepare for such a career, and shows how to succeed on the job. The book provides non-technical guidance for a successful career. The authors' extensive industrial experience is supplemented by insights from contributing authors from government and academia, Carol Joyce Blumberg, Leonard M. Gaines, Lynne B. Hare, William Q. Meeker, and Josef Schmee. Following an introductory chapter that provides an overview of the field, the authors discuss the various dimensions of a career in applied statistics in three succinct parts: The Work of a Statistician describes the day-to-day activities of applied statisticians in business and industry, official government, and various other application areas, highlighting the work environment and major on-the-job challenges Preparing for a Successful Career in Statistics describes the personal traits that characterize successful statisticians, the education that they need to acquire, and approaches for securing the right job Building a Successful Career as a Statistician offers practical guidance for addressing key challenges that statisticians face on the job, such as project initiation and execution, effective communication, publicizing successes, ethical considerations, and gathering good data; alternative career paths are also described The book concludes with an in-depth examination of careers for statisticians in academia as well as tips to help them stay on top of their field throughout their careers. Each chapter includes thought-provoking discussion questions and a Major Takeaways section that outlines key concepts. Real-world examples illustrate key points, and an FTP site provides additional information on selected topics. A Career in Statistics is an invaluable guide for individuals who are considering or have decided on a career in statistics as well as for statisticians already on the job who want to accelerate their path to success. It also serves as a suitable book for courses on statistical consulting, statistical practice, and statistics in the workplace at the undergraduate and graduate levels.
Author: Marie Davidian
Publisher: Springer
ISBN: 3319058010
Category : Mathematics
Languages : en
Pages : 579
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Book Description
This volume contains Raymond J. Carroll's research and commentary on its impact by leading statisticians. Each of the seven main parts focuses on a key research area: Measurement Error, Transformation and Weighting, Epidemiology, Nonparametric and Semiparametric Regression for Independent Data, Nonparametric and Semiparametric Regression for Dependent Data, Robustness, and other work. The seven subject areas reviewed in this book were chosen by Ray himself, as were the articles representing each area. The commentaries not only review Ray’s work, but are also filled with history and anecdotes. Raymond J. Carroll’s impact on statistics and numerous other fields of science is far-reaching. His vast catalog of work spans from fundamental contributions to statistical theory to innovative methodological development and new insights in disciplinary science. From the outset of his career, rather than taking the “safe” route of pursuing incremental advances, Ray has focused on tackling the most important challenges. In doing so, it is fair to say that he has defined a host of statistics areas, including weighting and transformation in regression, measurement error modeling, quantitative methods for nutritional epidemiology and non- and semiparametric regression.
Author: Douglas G. Altman
Publisher: CRC Press
ISBN: 1000228819
Category : Mathematics
Languages : en
Pages : 624
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Book Description
Practical Statistics for Medical Research is a problem-based text for medical researchers, medical students, and others in the medical arena who need to use statistics but have no specialized mathematics background. The author draws on twenty years of experience as a consulting medical statistician to provide clear explanations to key statistical concepts, with a firm emphasis on practical aspects of designing and analyzing medical research. Using real data and including dozens of interesting data sets, this bestselling text gives special attention to the presentation and interpretation of results and the many real problems that arise in medical research.
Author: Institute For Institute For Career Research
Publisher: Createspace Independent Publishing Platform
ISBN: 9781722767907
Category :
Languages : en
Pages : 34
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Book Description
STATISTICIANS USE MATHEMATICAL TECHNIQUES to collect and interpret information. The work is based on numbers, but unlike mathematicians who work on theoretical problems, statisticians use the numbers to solve real-life problems. Statisticians contribute to society in many ways. Some do serious work like finding ways to reduce hunger and disease, or studying the effects of global climate change on food supplies. Others help professional athletes up their game or help political candidates get elected. The biggest employer of statisticians is the federal government. Government statisticians work in just about every agency. For example, the Department of Labor has a large staff of statisticians studying things like employment rates, wage changes, growing and shrinking job sectors, and the demographic makeup of the workforce. The Department of Agriculture needs to know about crop conditions, livestock inventories, and how crops can be used for new products, and no mission at NASA proceeds without the thumbs up from their staff of statisticians. There is an obvious need for statisticians across all levels of government, but the demand is even greater outside the public sector. Statistical skills can be used to draw valuable insights from data in just about any industry. In fact, roughly 90 percent of America's industries use statistics in their daily operations. Since the advent of the computer, organizations of all kinds have been collecting and handling huge amounts of data. Computers can crunch the numbers, but statisticians are needed to analyze and interpret the data. They turn data into usable information that non-statisticians can understand and use to make good decisions. Statistics is the basis of one of the oldest professions in the world. Statistics were used to curb the spread of epidemics in the Middle Ages, and even ancient empires used them to track things like their populations, taxes, and important commodities like cattle. Yet the time has never been better to be a statistician. The career opportunities are so diverse, that statisticians can apply their knowledge to nearly any area they are passionate about. The demand for statisticians is at an all-time high. Employment for statisticians is growing fast, and so are their salaries. The median salary for those with less than three years of experience is $80,000, and that amount can double after being in the profession for at least nine years.
Author: Kevin P. Murphy
Publisher: MIT Press
ISBN: 0262018020
Category : Computers
Languages : en
Pages : 1102
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Book Description
A comprehensive introduction to machine learning that uses probabilistic models and inference as a unifying approach. Today's Web-enabled deluge of electronic data calls for automated methods of data analysis. Machine learning provides these, developing methods that can automatically detect patterns in data and then use the uncovered patterns to predict future data. This textbook offers a comprehensive and self-contained introduction to the field of machine learning, based on a unified, probabilistic approach. The coverage combines breadth and depth, offering necessary background material on such topics as probability, optimization, and linear algebra as well as discussion of recent developments in the field, including conditional random fields, L1 regularization, and deep learning. The book is written in an informal, accessible style, complete with pseudo-code for the most important algorithms. All topics are copiously illustrated with color images and worked examples drawn from such application domains as biology, text processing, computer vision, and robotics. Rather than providing a cookbook of different heuristic methods, the book stresses a principled model-based approach, often using the language of graphical models to specify models in a concise and intuitive way. Almost all the models described have been implemented in a MATLAB software package—PMTK (probabilistic modeling toolkit)—that is freely available online. The book is suitable for upper-level undergraduates with an introductory-level college math background and beginning graduate students.
Author: Francis Yuen
Publisher: Cognella Academic Publishing
ISBN: 9781516531226
Category :
Languages : en
Pages :
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Book Description
Conceptual and Practical Research and Statistics for Social Workers prepares students to intuitively theorize and utilize research and statistics within their social work practice. The book fosters the skills, savvy, and knowledge students need to interpret, apply, and produce studies within the discipline, enhancing their ability to become better consumers and producers of social work research. The book features two main sections, Research and Statistics, and its organization reflects the basic research process. The text begins with coverage of research questions and design and then introduces various data collection methods and instruments. Students then learn how to effectively analyze data and report and disseminate key findings. Throughout, readers build their understanding of methodological, ethical, and logical concepts in research and statistics, become familiar with basic needs assessment and program evaluation, develop the ability to choose appropriate statistics, and more. Employing everyday language, social work examples, metaphors, humor, and visual mapping, Conceptual and Practical Research and Statistics for Social Workers helps students tap into their critical thinking and problem-solving skills to develop key competencies. The text is an ideal resource for both undergraduate and graduate-level programs in social work.
Author: Amy Batchelor
Publisher: Columbia University Press
ISBN: 0231550227
Category : Social Science
Languages : en
Pages : 143
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Book Description
Understanding statistical concepts is essential for social work professionals. It is key to understanding research and reaching evidence-based decisions in your own practice—but that is only the beginning. If you understand statistics, you can determine the best interventions for your clients. You can use new tools to monitor and evaluate the progress of your client or team. You can recognize biased systems masked by complex models and the appearance of scientific neutrality. For social workers, statistics are not just math, they are a critical practice tool. This concise and approachable introduction to statistics limits its coverage to the concepts most relevant to social workers. Statistics in Social Work guides students through concepts and procedures from descriptive statistics and correlation to hypothesis testing and inferential statistics. Besides presenting key concepts, it focuses on real-world examples that students will encounter in a social work practice. Using concrete illustrations from a variety of potential concentrations and populations, Amy Batchelor creates clear connections between theory and practice—and demonstrates the important contributions statistics can make to evidence-based and rigorous social work practice.
Author: Amanda L. Golbeck
Publisher: CRC Press
ISBN: 1482236451
Category : Mathematics
Languages : en
Pages : 463
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Book Description
Learn How to Infuse Leadership into Your Passion for Scientific Research Leadership and Women in Statistics explores the role of statisticians as leaders, with particular attention to women statisticians as leaders. By paying special attention to women's issues, this book provides a clear vision for the future of women as leaders in scientific and
Author: Peter Bruce
Publisher: "O'Reilly Media, Inc."
ISBN: 1491952911
Category : Computers
Languages : en
Pages : 395
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Book Description
Statistical methods are a key part of of data science, yet very few data scientists have any formal statistics training. Courses and books on basic statistics rarely cover the topic from a data science perspective. This practical guide explains how to apply various statistical methods to data science, tells you how to avoid their misuse, and gives you advice on what's important and what's not. Many data science resources incorporate statistical methods but lack a deeper statistical perspective. If you’re familiar with the R programming language, and have some exposure to statistics, this quick reference bridges the gap in an accessible, readable format. With this book, you’ll learn: Why exploratory data analysis is a key preliminary step in data science How random sampling can reduce bias and yield a higher quality dataset, even with big data How the principles of experimental design yield definitive answers to questions How to use regression to estimate outcomes and detect anomalies Key classification techniques for predicting which categories a record belongs to Statistical machine learning methods that “learn” from data Unsupervised learning methods for extracting meaning from unlabeled data
