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Building Your Career as a Statistician

Author: Craig Mallinckrodt

Publisher: CRC Press

Published: 2023-08-01

Total Pages: 208

ISBN-13: 1000918629

This book is intended for anyone who is considering a career in statistics or a related field, or those at any point in their career with sufficient work time remaining such that investing in additional learning could be beneficial. As such, the book would be suitable for anyone pursing an MS or PhD in statistics or those already working in statistics. The book focuses on the non-statistical aspects of being a statistician that are crucial for success. These factors include 1) productivity and prioritization, 2) innovation and creativity, 3) communication, 4) critical thinking and decisions under uncertainty, 5) influence and leadership, 6) working relationships, and 7) career planning and continued learning. Each of these chapters includes sections on foundational principles and a section on putting those principles into practice. Connections between these individual skills are emphasized such that the reader can appreciate how the skills build upon each other leading to a whole that is greater than the sum of its parts. By including the individual perspectives from other experts on the fundamental principles and their application, readers will have a well-rounded view on how to build upon and fully leverage their technical skills in statistics. The primary audience for the book is large and diverse. It will be useful for self-study by virtually any statistician, but could also be used as a text in a graduate program that includes a course on careers and career development. Key Features: Takes principles proven to be useful in other settings and applies them to statisticians and statistical settings. Focused Concise Accessible to all levels, from grad students to mid-later career statisticians.

A Career in Statistics

Author: Gerald J. Hahn

Publisher: John Wiley & Sons

Published: 2012-08-29

Total Pages: 358

ISBN-13: 1118490134

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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.

Machine Learning

Author: Kevin P. Murphy

Publisher: MIT Press

Published: 2012-08-24

Total Pages: 1102

ISBN-13: 0262018020

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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.

The Career of a Research Statistician

Author: Shelemyahu Zacks

Publisher: Springer Nature

Published: 2020-03-13

Total Pages: 217

ISBN-13: 3030394344

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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.

Statistical Consulting

Author: Javier Cabrera

Publisher: Springer Science & Business Media

Published: 2013-04-17

Total Pages: 397

ISBN-13: 1475736630

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This book is intended for the statistician or student interested in becoming a statistical consultant, as well as clients who need to understand what is involved in the consulting process. It discusses different consulting environments, provides detailed descriptions of communication skills a consultant must possess, and provides concrete examples and case-studies of varying complexity. Emphasis is placed on the importance of engaging the client's understanding of the purpose and interpretation of statistical procedures.

Naked Statistics: Stripping the Dread from the Data

Author: Charles Wheelan

Publisher: W. W. Norton & Company

Published: 2013-01-07

Total Pages: 320

ISBN-13: 0393089827

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A New York Times bestseller "Brilliant, funny…the best math teacher you never had." —San Francisco Chronicle Once considered tedious, the field of statistics is rapidly evolving into a discipline Hal Varian, chief economist at Google, has actually called "sexy." From batting averages and political polls to game shows and medical research, the real-world application of statistics continues to grow by leaps and bounds. How can we catch schools that cheat on standardized tests? How does Netflix know which movies you’ll like? What is causing the rising incidence of autism? As best-selling author Charles Wheelan shows us in Naked Statistics, the right data and a few well-chosen statistical tools can help us answer these questions and more. For those who slept through Stats 101, this book is a lifesaver. Wheelan strips away the arcane and technical details and focuses on the underlying intuition that drives statistical analysis. He clarifies key concepts such as inference, correlation, and regression analysis, reveals how biased or careless parties can manipulate or misrepresent data, and shows us how brilliant and creative researchers are exploiting the valuable data from natural experiments to tackle thorny questions. And in Wheelan’s trademark style, there’s not a dull page in sight. You’ll encounter clever Schlitz Beer marketers leveraging basic probability, an International Sausage Festival illuminating the tenets of the central limit theorem, and a head-scratching choice from the famous game show Let’s Make a Deal—and you’ll come away with insights each time. With the wit, accessibility, and sheer fun that turned Naked Economics into a bestseller, Wheelan defies the odds yet again by bringing another essential, formerly unglamorous discipline to life.

Practical Statistics for Data Scientists

Author: Peter Bruce

Publisher: "O'Reilly Media, Inc."

Published: 2017-05-10

Total Pages: 395

ISBN-13: 1491952911

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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

The Real Work of Data Science

Author: Ron S. Kenett

Publisher: John Wiley & Sons

Published: 2019-04-01

Total Pages: 142

ISBN-13: 111957076X

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The essential guide for data scientists and for leaders who must get more from their data science teams The Economist boldly claims that data are now "the world's most valuable resource." But, as Kenett and Redman so richly describe, unlocking that value requires far more than technical excellence. The Real Work of Data Science explores understanding the problems, dealing with quality issues, building trust with decision makers, putting data science teams in the right organizational spots, and helping companies become data-driven. This is the work that spells the difference between a good data scientist and a great one, between a team that makes marginal contributions and one that drives the business, between a company that gains some value from its data and one in which data truly is "the most valuable resource." "These two authors are world-class experts on analytics, data management, and data quality; they've forgotten more about these topics than most of us will ever know. Their book is pragmatic, understandable, and focused on what really counts. If you want to do data science in any capacity, you need to read it." —Thomas H. Davenport, Distinguished Professor, Babson College and Fellow, MIT Initiative on the Digital Economy "I like your book. The chapters address problems that have faced statisticians for generations, updated to reflect today's issues, such as computational Big Data." —Sir David Cox, Warden of Nuffield College and Professor of Statistics, Oxford University "Data science is critical for competitiveness, for good government, for correct decisions. But what is data science? Kenett and Redman give, by far, the best introduction to the subject I have seen anywhere. They address the critical questions of formulating the right problem, collecting the right data, doing the right analyses, making the right decisions, and measuring the actual impact of the decisions. This book should become required reading in statistics and computer science departments, business schools, analytics institutes and, most importantly, by all business managers." —A. Blanton Godfrey, Joseph D. Moore Distinguished University Professor, Wilson College of Textiles, North Carolina State University

Black Enterprise Guide to Building Your Career

Author: Cassandra Hayes

Publisher: John Wiley & Sons

Published: 2002-07-17

Total Pages: 269

ISBN-13: 0471211907

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The African American's 411 on choosing, landing, and bulletproofing your career Do you long for a satisfying career but just don't know how to make the transition? Have you recently earned your degree, only to ask yourself, "What now?" Are your skills so narrowly defined that you'll be an easy target for downsizing? Whether you're just starting out or starting over, make yourself indispensable in today's workforce with the Black Enterprise Guide to Building Your Career. With the help of questionnaires, aptitude summaries, and sidebar profiles of successful African American professionals, you'll learn how to: * Decide which career path is right for you, including corporate and not-for-profit jobs and entrepreneurship opportunities * Tailor your resume to fit your goals * Negotiate the best salary and benefits * Network with other black professionals * Navigate career transitions * Prepare yourself with information before you go on the interview * Discover current Web sites for African Americans that offer career advice and employment information * And much more! Give your career the jump-start it needs with the essential tips and advice found in the Black Enterprise Guide to Building Your Career. Special Bonus To keep you abreast of the latest business and money management information, Black Enterprise is pleased to offer: * A free issue of Black Enterprise magazine * A free Wealth Building Kit (See inside coupons for details.)

Statistical Inference as Severe Testing

Author: Deborah G. Mayo

Publisher: Cambridge University Press

Published: 2018-09-20

Total Pages: 503

ISBN-13: 1108563309

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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.