Ethical Practice Of Statistics And Data Science

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Ethical Practice of Statistics and Data Science

Author : Rochelle Tractenberg
Publisher : Ethics International Press
Page : 685 pages
File Size : 46,7 Mb
Release : 2022-10-25
Category : Language Arts & Disciplines
ISBN : 9781804410776

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Ethical Practice of Statistics and Data Science by Rochelle Tractenberg Pdf

Ethical Practice of Statistics and Data Science is intended to prepare people to fully assume their responsibilities to practice statistics and data science ethically. Aimed at early career professionals, practitioners, and mentors or supervisors of practitioners, the book supports the ethical practice of statistics and data science, with an emphasis on how to earn the designation of, and recognize, “the ethical practitioner”. The book features 47 case studies, each mapped to the Data Science Ethics Checklist (DSEC); Data Ethics Framework (DEFW); the American Statistical Association (ASA) Ethical Guidelines for Statistical Practice; and the Association of Computing Machinery (ACM) Code of Ethics. It is necessary reading for students enrolled in any data intensive program, including undergraduate or graduate degrees in (bio-)statistics, business/analytics, or data science. Managers, leaders, supervisors, and mentors who lead data-intensive teams in government, industry, or academia would also benefit greatly from this book. This is a companion volume to Ethical Reasoning For A Data-Centered World, also published by Ethics International Press (2022). These are the first and only books to be based on, and to provide guidance to, the ASA and ACM Ethical Guidelines/Code of Ethics.

Ethical Practice of Statistics and Data Science

Author : Rochelle Tractenberg
Publisher : Unknown
Page : 0 pages
File Size : 46,8 Mb
Release : 2023
Category : Electronic
ISBN : 1804412678

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Ethical Practice of Statistics and Data Science by Rochelle Tractenberg Pdf

Ethical Practice of Statistics and Data Science is intended to prepare people to fully assume their responsibilities to practice statistics and data science ethically. Aimed at early career professionals, practitioners, and mentors or supervisors of practitioners, the book supports the ethical practice of statistics and data science, with an emphasis on how to earn the designation of, and recognize, the ethical practitioner . The book features 47 case studies, each mapped to the Data Science Ethics Checklist (DSEC); Data Ethics Framework (DEFW); the American Statistical Association (ASA) Ethical Guidelines for Statistical Practice; and the Association of Computing Machinery (ACM) Code of Ethics. It is necessary reading for students enrolled in any data intensive program, including undergraduate or graduate degrees in (bio-)statistics, business/analytics, or data science. Managers, leaders, supervisors, and mentors who lead data-intensive teams in government, industry, or academia would also benefit greatly from this book. This is a companion volume to Ethical Reasoning For A Data-Centered World, also published by Ethics International Press (2022). These are the first and only books to be based on, and to provide guidance to, the ASA and ACM Ethical Guidelines/Code of Ethics.

Ethical Reasoning for a Data-Centered World

Author : Rochelle Tractenberg
Publisher : Ethics International Press
Page : 411 pages
File Size : 49,7 Mb
Release : 2022-10-25
Category : Language Arts & Disciplines
ISBN : 9781804410790

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Ethical Reasoning for a Data-Centered World by Rochelle Tractenberg Pdf

The American Statistical Association (ASA) and the Association of Computing Machinery (ACM) have longstanding ethical practice standards that are explicitly intended to be utilized by all who use statistical practices or computing, or both. Since statistics and computing are critical in any data-centered activity, these practice standards are essential to instruction in the uses of statistical practices or computing across disciplines. Ethical Reasoning For A Data-Centered World is aimed at any undergraduate or graduate students utilizing data. Whether the career goal is research, teaching, business, government, or a combination, this book presents a method for understanding and prioritizing ethical statistics, computing, and data science – featuring the ASA and ACM practice standards. To facilitate engagement, integration with prior learning, and authenticity, the material is organized around seven tasks: Planning/Designing; Data collection; Analysis; Interpretation; Reporting; Documenting; and Engaging in team work. This book is a companion volume to Ethical Practice of Statistics and Data Science, also published by Ethics International Press (2022). These are the first and only books to be based on, and to provide guidance to, the American Statistical Association (ASA) and Association of Computing Machinery (ACM) ethical guideline documents.

Ethical Reasoning for a Data-Centered World

Author : Rochelle Tractenberg
Publisher : Unknown
Page : 0 pages
File Size : 48,5 Mb
Release : 2023
Category : Electronic
ISBN : 1804412686

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Ethical Reasoning for a Data-Centered World by Rochelle Tractenberg Pdf

The American Statistical Association (ASA) and the Association of Computing Machinery (ACM) have longstanding ethical practice standards that are explicitly intended to be utilized by all who use statistical practices or computing, or both. Since statistics and computing are critical in any data-centered activity, these practice standards are essential to instruction in the uses of statistical practices or computing across disciplines. Ethical Reasoning For A Data-Centered World is aimed at any undergraduate or graduate students utilizing data. Whether the career goal is research, teaching, business, government, or a combination, this book presents a method for understanding and prioritizing ethical statistics, computing, and data science featuring the ASA and ACM practice standards. To facilitate engagement, integration with prior learning, and authenticity, the material is organized around seven tasks: Planning/Designing; Data collection; Analysis; Interpretation; Reporting; Documenting; and Engaging in team work. This book is a companion volume to Ethical Practice of Statistics and Data Science, also published by Ethics International Press (2022). These are the first and only books to be based on, and to provide guidance to, the American Statistical Association (ASA) and Association of Computing Machinery (ACM) ethical guideline documents.

Ethics and Data Science

Author : Mike Loukides,Hilary Mason,DJ Patil
Publisher : O'Reilly Media
Page : 40 pages
File Size : 48,7 Mb
Release : 2018-07-25
Category : Computers
ISBN : 9781492078227

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Ethics and Data Science by Mike Loukides,Hilary Mason,DJ Patil Pdf

As the impact of data science continues to grow on society there is an increased need to discuss how data is appropriately used and how to address misuse. Yet, ethical principles for working with data have been available for decades. The real issue today is how to put those principles into action. With this report, authors Mike Loukides, Hilary Mason, and DJ Patil examine practical ways for making ethical data standards part of your work every day. To help you consider all of possible ramifications of your work on data projects, this report includes: A sample checklist that you can adapt for your own procedures Five framing guidelines (the Five C’s) for building data products: consent, clarity, consistency, control, and consequences Suggestions for building ethics into your data-driven culture Now is the time to invest in a deliberate practice of data ethics, for better products, better teams, and better outcomes. Get a copy of this report and learn what it takes to do good data science today.

Applied Data Science

Author : Douglas G. Woolford,Donna Kotsopoulos,Boba Samuels
Publisher : Springer Nature
Page : 195 pages
File Size : 42,6 Mb
Release : 2023-05-09
Category : Computers
ISBN : 9783031299377

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Applied Data Science by Douglas G. Woolford,Donna Kotsopoulos,Boba Samuels Pdf

The use of data to guide action is growing. Even the public uses data to guide everyday decisions! How do we develop data acumen across a broad range of fields and varying levels of expertise? How do we foster the development of effective data translators? This book explores these questions, presenting an interdisciplinary collection of edited contributions across fields such as education, health sciences, natural sciences, politics, economics, business and management studies, social sciences, and humanities. Authors illustrate how to use data within a discipline, including visualization and analysis, translating and communicating results, and pedagogical considerations. This book is of interest to scholars and anyone looking to understand the use of data science across disciplines. It is ideal in a course for non-data science majors exploring how data translation occurs in various contexts and for professionals looking to engage in roles requiring data translation.

Education for the Professions in Times of Change

Author : Linda Clarke
Publisher : MDPI
Page : 186 pages
File Size : 50,9 Mb
Release : 2020-12-02
Category : Juvenile Nonfiction
ISBN : 9783039365159

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Education for the Professions in Times of Change by Linda Clarke Pdf

The eminent Harvard educationalist Howard Garner writes a preface to the Place Model within his Good Project Blog which provides a preface to this timely book. Professional is a slippery term, open to willful abuse, misuse and misunderstanding – as evidenced by the ways in which this chameleon term can be used as both a compliment and an insult. In this book academics from a range of professional fields deconstruct ‘professional’ and reimagine professionals in an age of rapid change where professionals are both increasingly in demand and frequently under threat. Several deploy the lens of Clarke’s Place Model to examine professions including teaching, midwifery, social work, journalism, and optometry. Some papers are empirical and some are based around using the Place Model as a thought experiment. All turn a critical eye on professionals and all find them to be, like all humans, neither devils nor divines (Maya Angelou), but at their best a combination of two indispensable characteristics, trustworthiness and expertise.

Data Science for Undergraduates

Author : National Academies of Sciences, Engineering, and Medicine,Division of Behavioral and Social Sciences and Education,Board on Science Education,Division on Engineering and Physical Sciences,Committee on Applied and Theoretical Statistics,Board on Mathematical Sciences and Analytics,Computer Science and Telecommunications Board,Committee on Envisioning the Data Science Discipline: The Undergraduate Perspective
Publisher : National Academies Press
Page : 139 pages
File Size : 47,6 Mb
Release : 2018-11-11
Category : Education
ISBN : 9780309475594

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Data Science for Undergraduates by National Academies of Sciences, Engineering, and Medicine,Division of Behavioral and Social Sciences and Education,Board on Science Education,Division on Engineering and Physical Sciences,Committee on Applied and Theoretical Statistics,Board on Mathematical Sciences and Analytics,Computer Science and Telecommunications Board,Committee on Envisioning the Data Science Discipline: The Undergraduate Perspective Pdf

Data science is emerging as a field that is revolutionizing science and industries alike. Work across nearly all domains is becoming more data driven, affecting both the jobs that are available and the skills that are required. As more data and ways of analyzing them become available, more aspects of the economy, society, and daily life will become dependent on data. It is imperative that educators, administrators, and students begin today to consider how to best prepare for and keep pace with this data-driven era of tomorrow. Undergraduate teaching, in particular, offers a critical link in offering more data science exposure to students and expanding the supply of data science talent. Data Science for Undergraduates: Opportunities and Options offers a vision for the emerging discipline of data science at the undergraduate level. This report outlines some considerations and approaches for academic institutions and others in the broader data science communities to help guide the ongoing transformation of this field.

Leadership in Statistics and Data Science

Author : Amanda L. Golbeck
Publisher : Springer Nature
Page : 432 pages
File Size : 40,7 Mb
Release : 2021-03-22
Category : Business & Economics
ISBN : 9783030600600

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Leadership in Statistics and Data Science by Amanda L. Golbeck Pdf

This edited collection brings together voices of the strongest thought leaders on diversity, equity and inclusion in the field of statistics and data science, with the goal of encouraging and steering the profession into the regular practice of inclusive and humanistic leadership. It provides futuristic ideas for promoting opportunities for equitable leadership, as well as tested approaches that have already been found to make a difference. It speaks to the challenges and opportunities of leading successful research collaborations and making strong connections within research teams. Curated with a vision that leadership takes a myriad of forms, and that diversity has many dimensions, this volume examines the nuances of leadership within a workplace environment and promotes storytelling and other competencies as critical elements of effective leadership. It makes the case for inclusive and humanistic leadership in statistics and data science, where there often remains a dearth of women and members of certain racial communities among the employees. Titled and non-titled leaders will benefit from the planning, evaluation, and structural tools offered within to contribute inclusive excellence in workplace climate, environment, and culture.

Responsible Data Science

Author : Peter C. Bruce,Grant Fleming
Publisher : John Wiley & Sons
Page : 304 pages
File Size : 52,6 Mb
Release : 2021-04-13
Category : Computers
ISBN : 9781119741770

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Responsible Data Science by Peter C. Bruce,Grant Fleming Pdf

Explore the most serious prevalent ethical issues in data science with this insightful new resource The increasing popularity of data science has resulted in numerous well-publicized cases of bias, injustice, and discrimination. The widespread deployment of “Black box” algorithms that are difficult or impossible to understand and explain, even for their developers, is a primary source of these unanticipated harms, making modern techniques and methods for manipulating large data sets seem sinister, even dangerous. When put in the hands of authoritarian governments, these algorithms have enabled suppression of political dissent and persecution of minorities. To prevent these harms, data scientists everywhere must come to understand how the algorithms that they build and deploy may harm certain groups or be unfair. Responsible Data Science delivers a comprehensive, practical treatment of how to implement data science solutions in an even-handed and ethical manner that minimizes the risk of undue harm to vulnerable members of society. Both data science practitioners and managers of analytics teams will learn how to: Improve model transparency, even for black box models Diagnose bias and unfairness within models using multiple metrics Audit projects to ensure fairness and minimize the possibility of unintended harm Perfect for data science practitioners, Responsible Data Science will also earn a spot on the bookshelves of technically inclined managers, software developers, and statisticians.

A Statistical Guide for the Ethically Perplexed

Author : Lawrence Hubert,Howard Wainer
Publisher : CRC Press
Page : 588 pages
File Size : 46,9 Mb
Release : 2012-09-25
Category : Mathematics
ISBN : 9781439873687

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A Statistical Guide for the Ethically Perplexed by Lawrence Hubert,Howard Wainer Pdf

For disciplines concerned with human well-being, such as medicine, psychology, and law, statistics must be used in accordance with standards for ethical practice. A Statistical Guide for the Ethically Perplexed illustrates the proper use of probabilistic and statistical reasoning in the behavioral, social, and biomedical sciences. Designed to be consulted when learning formal statistical techniques, the text describes common instances of both correct and false statistical and probabilistic reasoning. Lauded for their contributions to statistics, psychology, and psychometrics, the authors make statistical methods relevant to readers’ day-to-day lives by including real historical situations that demonstrate the role of statistics in reasoning and decision making. The historical vignettes encompass the English case of Sally Clark, breast cancer screening, risk and gambling, the Federal Rules of Evidence, "high-stakes" testing, regulatory issues in medicine, difficulties with observational studies, ethics in human experiments, health statistics, and much more. In addition to these topics, seven U.S. Supreme Court decisions reflect the influence of statistical and psychometric reasoning and interpretation/misinterpretation. Exploring the intersection of ethics and statistics, this comprehensive guide assists readers in becoming critical and ethical consumers and producers of statistical reasoning and analyses. It will help them reason correctly and use statistics in an ethical manner.

Data Science Ethics

Author : David Martens
Publisher : Oxford University Press
Page : 256 pages
File Size : 51,7 Mb
Release : 2022-03-24
Category : Computers
ISBN : 9780192663023

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Data Science Ethics by David Martens Pdf

Data science ethics is all about what is right and wrong when conducting data science. Data science has so far been primarily used for positive outcomes for businesses and society. However, just as with any technology, data science has also come with some negative consequences: an increase of privacy invasion, data-driven discrimination against sensitive groups, and decision making by complex models without explanations. While data scientists and business managers are not inherently unethical, they are not trained to weigh the ethical considerations that come from their work - Data Science Ethics addresses this increasingly significant gap and highlights different concepts and techniques that aid understanding, ranging from k-anonymity and differential privacy to homomorphic encryption and zero-knowledge proofs to address privacy concerns, techniques to remove discrimination against sensitive groups, and various explainable AI techniques. Real-life cautionary tales further illustrate the importance and potential impact of data science ethics, including tales of racist bots, search censoring, government backdoors, and face recognition. The book is punctuated with structured exercises that provide hypothetical scenarios and ethical dilemmas for reflection that teach readers how to balance the ethical concerns and the utility of data.

Modern Data Science with R

Author : Benjamin S. Baumer,Daniel T. Kaplan,Nicholas J. Horton
Publisher : CRC Press
Page : 830 pages
File Size : 52,5 Mb
Release : 2021-03-31
Category : Business & Economics
ISBN : 9780429575396

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Modern Data Science with R by Benjamin S. Baumer,Daniel T. Kaplan,Nicholas J. Horton Pdf

From a review of the first edition: "Modern Data Science with R... is rich with examples and is guided by a strong narrative voice. What’s more, it presents an organizing framework that makes a convincing argument that data science is a course distinct from applied statistics" (The American Statistician). Modern Data Science with R is a comprehensive data science textbook for undergraduates that incorporates statistical and computational thinking to solve real-world data problems. Rather than focus exclusively on case studies or programming syntax, this book illustrates how statistical programming in the state-of-the-art R/RStudio computing environment can be leveraged to extract meaningful information from a variety of data in the service of addressing compelling questions. The second edition is updated to reflect the growing influence of the tidyverse set of packages. All code in the book has been revised and styled to be more readable and easier to understand. New functionality from packages like sf, purrr, tidymodels, and tidytext is now integrated into the text. All chapters have been revised, and several have been split, re-organized, or re-imagined to meet the shifting landscape of best practice.

Modern Data Science with R

Author : Benjamin S. Baumer,Daniel T. Kaplan,Nicholas J. Horton
Publisher : CRC Press
Page : 650 pages
File Size : 41,6 Mb
Release : 2021-04-13
Category : Business & Economics
ISBN : 9780429577505

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Modern Data Science with R by Benjamin S. Baumer,Daniel T. Kaplan,Nicholas J. Horton Pdf

From a review of the first edition: "Modern Data Science with R... is rich with examples and is guided by a strong narrative voice. What’s more, it presents an organizing framework that makes a convincing argument that data science is a course distinct from applied statistics" (The American Statistician). Modern Data Science with R is a comprehensive data science textbook for undergraduates that incorporates statistical and computational thinking to solve real-world data problems. Rather than focus exclusively on case studies or programming syntax, this book illustrates how statistical programming in the state-of-the-art R/RStudio computing environment can be leveraged to extract meaningful information from a variety of data in the service of addressing compelling questions. The second edition is updated to reflect the growing influence of the tidyverse set of packages. All code in the book has been revised and styled to be more readable and easier to understand. New functionality from packages like sf, purrr, tidymodels, and tidytext is now integrated into the text. All chapters have been revised, and several have been split, re-organized, or re-imagined to meet the shifting landscape of best practice.

The Ethical Record

Author : Samuel Burns Weston
Publisher : Unknown
Page : 582 pages
File Size : 51,9 Mb
Release : 1890
Category : Ethical culture movement
ISBN : UOM:39015026264005

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The Ethical Record by Samuel Burns Weston Pdf