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| ethical guidelines for statistical practice: Ethics in Statistics Hassan Doosti, 2024-03-29 Data plays a vital role in different parts of our lives. In the world of big data, and policy determined by a variety of statistical artifacts, discussions around the ethics of data gathering, manipulation and presentation are increasingly important. Ethics in Statistics aims to make a significant contribution to that debate. The processes of gathering data through sampling, summarising of the findings, and extending results to a population, need to be checked via an ethical prospective, as well as a statistical one. Statistical learning without ethics can be harmful for mankind. This edited collection brings together contributors in the field of data science, data analytics and statistics, to share their thoughts about the role of ethics in different aspects of statistical learning. |
| ethical guidelines for statistical practice: Ethical Practice of Statistics and Data Science Rochelle Tractenberg, 2023-11-25 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 guidelines for statistical practice: Ethical Practice of Statistics and Data Science Rochelle Tractenberg, 2023 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 guidelines for statistical practice: Ethical Reasoning for a Data-Centered World Rochelle Tractenberg, 2023-11-25 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 guidelines for statistical practice: Research Methods and Statistics Janie H. Wilson, Shauna W. Joye, 2016-07-21 This innovative text offers a completely integrated approach to teaching research methods and statistics by presenting a research question accompanied by the appropriate methods and statistical procedures needed to address it. Research questions and designs become more complex as chapters progress, building on simpler questions to reinforce student learning. Using a conversational style and research examples from published works, this comprehensive book walks readers through the entire research process and includes ample pedagogical support for SPSS, Excel, and APA style. |
| ethical guidelines for statistical practice: Principles and Practices for a Federal Statistical Agency National Academies of Sciences, Engineering, and Medicine, Division of Behavioral and Social Sciences and Education, Committee on National Statistics, 2017-08-27 Publicly available statistics from government agencies that are credible, relevant, accurate, and timely are essential for policy makers, individuals, households, businesses, academic institutions, and other organizations to make informed decisions. Even more, the effective operation of a democratic system of government depends on the unhindered flow of statistical information to its citizens. In the United States, federal statistical agencies in cabinet departments and independent agencies are the governmental units whose principal function is to compile, analyze, and disseminate information for such statistical purposes as describing population characteristics and trends, planning and monitoring programs, and conducting research and evaluation. The work of these agencies is coordinated by the U.S. Office of Management and Budget. Statistical agencies may acquire information not only from surveys or censuses of people and organizations, but also from such sources as government administrative records, private-sector datasets, and Internet sources that are judged of suitable quality and relevance for statistical use. They may conduct analyses, but they do not advocate policies or take partisan positions. Statistical purposes for which they provide information relate to descriptions of groups and exclude any interest in or identification of an individual person, institution, or economic unit. Four principles are fundamental for a federal statistical agency: relevance to policy issues, credibility among data users, trust among data providers, and independence from political and other undue external influence. Principles and Practices for a Federal Statistical Agency: Sixth Edition presents and comments on these principles as they've been impacted by changes in laws, regulations, and other aspects of the environment of federal statistical agencies over the past 4 years. |
| ethical guidelines for statistical practice: The Handbook of Social Research Ethics Donna M. Mertens, Pauline E. Ginsberg, 2009 Brings together international scholars across the social and behavioural sciences and education to address those ethical issues that arise in the theory and practice of research within the technologically advancing and culturally complex world in which we live. |
| ethical guidelines for statistical practice: Ethical Choices in Research Harris M. Cooper, 2016 Many books discuss the ethical treatment of human subjects in behavioral research, yet few talk about the equally important ethical issues that arise when the data are being analyzed and the study is being written up. All researchers need to be aware of their professional responsibilities and make sound choices after the subjects have left. This practical and easy-to-follow guide walks readers through often overlooked decision points in the research process. Drawing from his extensive experience as a teacher of research methods and a senior editorial advisor, and from well-established standards of practice -- including the APA Ethics Code -- Harris Cooper is the ideal mentor in this process. Readers of this book will learn how to: Collect and manage data in a way that does not compromise the confidentiality of subjects Avoid data fraud and misleading data analysis Assign research responsibilities and authorships to team members Avoid committing plagiarism and intellectual theft Navigate the journal submission and publication process Post-publication ethical considerations are also addressed, including researchers' obligations when communicating their findings to the media and the general public, and when engaging with the scientific community as a peer reviewer. |
| ethical guidelines for statistical practice: Registries for Evaluating Patient Outcomes Agency for Healthcare Research and Quality/AHRQ, 2014-04-01 This User’s Guide is intended to support the design, implementation, analysis, interpretation, and quality evaluation of registries created to increase understanding of patient outcomes. For the purposes of this guide, a patient registry is an organized system that uses observational study methods to collect uniform data (clinical and other) to evaluate specified outcomes for a population defined by a particular disease, condition, or exposure, and that serves one or more predetermined scientific, clinical, or policy purposes. A registry database is a file (or files) derived from the registry. Although registries can serve many purposes, this guide focuses on registries created for one or more of the following purposes: to describe the natural history of disease, to determine clinical effectiveness or cost-effectiveness of health care products and services, to measure or monitor safety and harm, and/or to measure quality of care. Registries are classified according to how their populations are defined. For example, product registries include patients who have been exposed to biopharmaceutical products or medical devices. Health services registries consist of patients who have had a common procedure, clinical encounter, or hospitalization. Disease or condition registries are defined by patients having the same diagnosis, such as cystic fibrosis or heart failure. The User’s Guide was created by researchers affiliated with AHRQ’s Effective Health Care Program, particularly those who participated in AHRQ’s DEcIDE (Developing Evidence to Inform Decisions About Effectiveness) program. Chapters were subject to multiple internal and external independent reviews. |
| ethical guidelines for statistical practice: Good Statistical Practice for Natural Resources Research Roger Stern, 2004 Part 1: Introduction Chapter 1: What is Natural Resources Research? Chapter 2: At Least Read This. Chapter 3: Sidetracks Part 2: Planning Chapter 4: Introduction to Research Planning Chapter 5: Concepts Underlying Experiments Chapter 6: Sampling Concepts Chapter 7: Surveys and Studies of Human Subjects Chapter 8: Surveying Land and Natural Populations Chapter 9: Planning Effective Experiments Part 3: Data Management Chapter 10: Data Management Issues and Problems Chapter 11: Use of Spreadsheet Packages Chapter 12: The Role of a Database Package Chapter 13: Developing a Data Management Strategy Chapter 14: Use of Statistical Software Part 4: Analysis Chapter 15: Analysis - Aims and Approaches Chapter 16: The DIY Toolbox - General Ideas 16.1 Opening the Toolbox 221 Chapter 17: Analysis of Survey Data Chapter 18: Analysis of Experimental Data Chapter 19: General Linear Models Chapter 20: The Craftsman's Toolbox Chapter 21: Informative Presentation of Tables, Graphs and Statistics Part 5: Where Next? Chapter 22: Current Trends and their Implications for Good Practice Chapter 23: Resources and Further Reading. |
| ethical guidelines for statistical practice: International Ethical Guidelines for Health-Related Research Involving Humans Council for International Organizations of Medical Sciences (CIOMS), 2017-01-31 In the new 2016 version of the ethical guidelines, CIOMS provides answers to a number of pressing issues in research ethics. The Council does so by stressing the need for research having scientific and social value, by providing special guidelines for health-related research in low-resource settings, by detailing the provisions for involving vulnerable groups in research and for describing under what conditions biological samples and health-related data can be used for research.--Page 4 de la couverture. |
| ethical guidelines for statistical practice: Handbook of Ethics in Quantitative Methodology A. T. Panter, 2011-03-01 This comprehensive Handbook is the first to provide a practical, interdisciplinary review of ethical issues as they relate to quantitative methodology including how to present evidence for reliability and validity, what comprises an adequate tested population, and what constitutes scientific knowledge for eliminating biases. The book uses an ethical framework that emphasizes the human cost of quantitative decision making to help researchers understand the specific implications of their choices. The order of the Handbook chapters parallels the chronology of the research process: determining the research design and data collection; data analysis; and communicating findings. Each chapter: Explores the ethics of a particular topic Identifies prevailing methodological issues Reviews strategies and approaches for handling such issues and their ethical implications Provides one or more case examples Outlines plausible approaches to the issue including best-practice solutions. Part 1 presents ethical frameworks that cross-cut design, analysis, and modeling in the behavioral sciences. Part 2 focuses on ideas for disseminating ethical training in statistics courses. Part 3 considers the ethical aspects of selecting measurement instruments and sample size planning and explores issues related to high stakes testing, the defensibility of experimental vs. quasi-experimental research designs, and ethics in program evaluation. Decision points that shape a researchers’ approach to data analysis are examined in Part 4 – when and why analysts need to account for how the sample was selected, how to evaluate tradeoffs of hypothesis-testing vs. estimation, and how to handle missing data. Ethical issues that arise when using techniques such as factor analysis or multilevel modeling and when making causal inferences are also explored. The book concludes with ethical aspects of reporting meta-analyses, of cross-disciplinary statistical reform, and of the publication process. This Handbook appeals to researchers and practitioners in psychology, human development, family studies, health, education, sociology, social work, political science, and business/marketing. This book is also a valuable supplement for quantitative methods courses required of all graduate students in these fields. |
| ethical guidelines for statistical practice: Leadership and Women in Statistics Amanda L. Golbeck, Ingram Olkin, Yulia R. Gel, 2015-07-13 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 |
| ethical guidelines for statistical practice: A Statistical Guide for the Ethically Perplexed Lawrence Hubert, Howard Wainer, 2012-09-25 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. |
| ethical guidelines for statistical practice: Modern Statistics with R Måns Thulin, 2024 The past decades have transformed the world of statistical data analysis, with new methods, new types of data, and new computational tools. Modern Statistics with R introduces you to key parts of this modern statistical toolkit. It teaches you: Data wrangling - importing, formatting, reshaping, merging, and filtering data in R. Exploratory data analysis - using visualisations and multivariate techniques to explore datasets. Statistical inference - modern methods for testing hypotheses and computing confidence intervals. Predictive modelling - regression models and machine learning methods for prediction, classification, and forecasting. Simulation - using simulation techniques for sample size computations and evaluations of statistical methods. Ethics in statistics - ethical issues and good statistical practice. R programming - writing code that is fast, readable, and (hopefully!) free from bugs. No prior programming experience is necessary. Clear explanations and examples are provided to accommodate readers at all levels of familiarity with statistical principles and coding practices. A basic understanding of probability theory can enhance comprehension of certain concepts discussed within this book. In addition to plenty of examples, the book includes more than 200 exercises, with fully worked solutions available at: www.modernstatisticswithr.com. |
| ethical guidelines for statistical practice: Essentials of Business Statistics Bruce Bowerman, 2014-01-03 The primary goal of Essentials of Business Statistics is to illustrate an accurate view of business statistics in a way that students can easily understand. This is achieved in the following ways: New statistical topics and tools are introduced by using continuing case studies. This approach helps to alleviate student anxiety in learning new concepts and enhances overall comprehension Streamlined and clarified coverage of graphical and numerical methods New graphically based procedures for finding confidence intervals and performing hypothesis tests Increased emphasis on Excel and MINITAB with improved and updated step-by-step instructions in the end of chapter material Connect Business Statistics homework management |
| ethical guidelines for statistical practice: 100 Questions (and Answers) About Research Ethics Emily E. Anderson, Amy Corneli, 2017-12-05 100 Questions (and Answers) About Research Ethics by Emily E Anderson and Amy Corneli is an essential guide for graduate students and researchers in the social and behavioral sciences. It identifies ethical issues that individuals must consider when planning research studies as well as provides guidance on how to address ethical issues that might arise during research implementation. Questions such as assessing risks, to protecting privacy and vulnerable populations, obtaining informed consent, using technology including social media, negotiating the IRB process, and handling data ethically are covered. Acting as a resource for students developing their thesis and dissertation proposals and for junior faculty designing research, this book reflects the latest U.S. federal research regulations to take effect mostly in January 2018. |
| ethical guidelines for statistical practice: The Ethical Use of Data in Education Ellen B. Mandinach, Edith S. Gummer, 2021 This volume brings together experts on various aspects of education to address many of the emerging issues and problems that affect how data are being used or misused in educational contexts. Readers will learn about the importance of using data effectively, responsibly, and ethically to fully understand how cognitive fallacies occur and how they impact decisionmaking. They will understand how codes of ethics deal with the use of data within education as well as in other disciplines. Chapters provide a landscape view of the regulations that pertain to data use and policies that have emerged, including the impact of accountability on data use and data ethics. The text covers data ethics in local education agencies, professional development, educator preparation, testing programs, and educational technology. Chapter authors recommend steps to improve awareness among educators, stakeholders, and other interested groups and suggest actions that can be taken to enhance educators’ capacity to use data responsibly. A final use case chapter describes the importance of data ethics in terms of equity in schools and includes salient examples of ethical dilemmas, with questions and reflections on how ethics and equity apply to each situation. The conclusion addresses data ethics in terms of professionalism and poses several recommendations to challenge educators in ways to raise awareness of and integrate data ethics into educational practice. Book Features: Discusses how accountability affects effective data, including the pressure on schools and districts to perform better on test scores or other indicators. Outlines ten recommendations for how professional development can incorporate data ethics in practice.Reviews the expectations and realities of preparing educators for data literacy, including an example of one teacher education program’s integrated, curriculum-wide approach. Considers the role of testing companies in ethical data use, including issues around equity in assessment data.Explores how educational technologies, platforms, and applications impact data use. Contributors: Wayne Camara, Michelle Croft, Amanda Datnow, Chris Dede, Edward Dieterle, Sherman Dorn, Paul Gibbs, Edith S. Gummer, Beth Holland, Taryn A. Hochleitner, Jo Beth Jimerson, Marie Lockton, Ellen B. Mandinach, Sharon L. Nichols, Diana Nunnaley, Brennan McMahon Parton, Amelia Vance, Alina von Davier, Casey Waughn, Haley Weddle |
| ethical guidelines for statistical practice: Modern Statistics with R Måns Thulin, 2024-08-20 The past decades have transformed the world of statistical data analysis, with new methods, new types of data, and new computational tools. Modern Statistics with R introduces you to key parts of this modern statistical toolkit. It teaches you: Data wrangling – importing, formatting, reshaping, merging, and filtering data in R. Exploratory data analysis – using visualisations and multivariate techniques to explore datasets. Statistical inference – modern methods for testing hypotheses and computing confidence intervals. Predictive modelling – regression models and machine learning methods for prediction, classification, and forecasting. Simulation – using simulation techniques for sample size computations and evaluations of statistical methods. Ethics in statistics – ethical issues and good statistical practice. R programming – writing code that is fast, readable, and (hopefully!) free from bugs. No prior programming experience is necessary. Clear explanations and examples are provided to accommodate readers at all levels of familiarity with statistical principles and coding practices. A basic understanding of probability theory can enhance comprehension of certain concepts discussed within this book. In addition to plenty of examples, the book includes more than 200 exercises, with fully worked solutions available at: www.modernstatisticswithr.com. |
| ethical guidelines for statistical practice: Ebook: Business Statistics in Practice: Using Data, Modeling and Analytics Bowerman, 2016-04-16 Ebook: Business Statistics in Practice: Using Data, Modeling and Analytics |
| ethical guidelines for statistical practice: Modern Data Science with R Benjamin S. Baumer, Daniel T. Kaplan, Nicholas J. Horton, 2021-03-31 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. |
| ethical guidelines for statistical practice: Responsible Conduct of Research Adil E. Shamoo, David B. Resnik, 2009-02-12 Recent scandals and controversies, such as data fabrication in federally funded science, data manipulation and distortion in private industry, and human embryonic stem cell research, illustrate the importance of ethics in science. Responsible Conduct of Research, now in a completely updated second edition, provides an introduction to the social, ethical, and legal issues facing scientists today. |
| ethical guidelines for statistical practice: Education for the Professions in Times of Change Linda Clarke, 2020-12-02 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. |
| ethical guidelines for statistical practice: Applications in Statistical Computing Nadja Bauer, Katja Ickstadt, Karsten Lübke, Gero Szepannek, Heike Trautmann, Maurizio Vichi, 2019-10-12 This volume presents a selection of research papers on various topics at the interface of statistics and computer science. Emphasis is put on the practical applications of statistical methods in various disciplines, using machine learning and other computational methods. The book covers fields of research including the design of experiments, computational statistics, music data analysis, statistical process control, biometrics, industrial engineering, and econometrics. Gathering innovative, high-quality and scientifically relevant contributions, the volume was published in honor of Claus Weihs, Professor of Computational Statistics at TU Dortmund University, on the occasion of his 66th birthday. |
| ethical guidelines for statistical practice: Ethics in Econometrics Philip Hans Franses, 2024-06-30 Econometricians make choices on data, models, and estimation routines. Using various examples, this book shows the consequences of choices. |
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| ethical guidelines for statistical practice: Ethics in Scientific Research Cortney Weinbaum, Carlos Ignacio Gutierrez, 2019-06-05 Scientific research ethics vary by discipline and by country, and this analysis sought to understand those variations. The authors reviewed literature and conducted interviews to provide researchers, government officials, and others who create, modify, and enforce ethics in scientific research around the world with an understanding of how ethics are created, monitored, and enforced across scientific disciplines and across international borders. |
| ethical guidelines for statistical practice: Introduction to Python Programming for Business and Social Science Applications Frederick Kaefer, Paul Kaefer, 2020-08-06 Would you like to gather big datasets, analyze them, and visualize the results, all in one program? If this describes you, then Introduction to Python Programming for Business and Social Science Applications is the book for you. Authors Frederick Kaefer and Paul Kaefer walk you through each step of the Python package installation and analysis process, with frequent exercises throughout so you can immediately try out the functions you’ve learned. Written in straightforward language for those with no programming background, this book will teach you how to use Python for your research and data analysis. Instead of teaching you the principles and practices of programming as a whole, this application-oriented text focuses on only what you need to know to research and answer social science questions. The text features two types of examples, one set from the General Social Survey and one set from a large taxi trip dataset from a major metropolitan area, to help readers understand the possibilities of working with Python. Chapters on installing and working within a programming environment, basic skills, and necessary commands will get you up and running quickly, while chapters on programming logic, data input and output, and data frames help you establish the basic framework for conducting analyses. Further chapters on web scraping, statistical analysis, machine learning, and data visualization help you apply your skills to your research. More advanced information on developing graphical user interfaces (GUIs) help you create functional data products using Python to inform general users of data who don’t work within Python. First there was IBM® SPSS®, then there was R, and now there′s Python. Statistical software is getting more aggressive - let authors Frederick Kaefer and Paul Kaefer help you tame it with Introduction to Python Programming for Business and Social Science Applications. |
| ethical guidelines for statistical practice: Practicing Research Arlene Fink, 2008 Provides methods for determining the validity of evidence and how to justify an acceptable level of proof based on science, experience, and values |
| ethical guidelines for statistical practice: Integrated Research Methods In Public Health Muriel J. Harris, Baraka Muvuka, 2022-11-01 Explore an integrated approach to public health research methods In Integrated Research Methods in Public Health, a team of eminent public health researchers delivers an eye-opening exploration of public health research methods presented with integrative approaches to teaching that facilitate holistic and transformative learning experiences. The methods used in this book enable students to make connections between concepts and content areas more readily than with traditional approaches. In this book, readers will find extensive use of the concept of the co-construction of learning, in which the active participation of students and instructors in an interactive, varied, and student-centered learning environment is achieved. It also includes: Mini case studies, team learning exercises and worksheets, and group project outlines Literature reviews that showcase the latest developments in the research on the subject Integrated considerations of ethical issues, cultural responsiveness, theoretical foundations, and philosophical underpinnings Perfect for senior undergraduate and graduate students in public health, Integrated Research Methods in Public Health will also earn a place in the libraries of public health and social science academics and researchers, as well as public health practitioners and professionals working in non-profit organizations with public-health related services. |
| ethical guidelines for statistical practice: Glittering Vices Rebecca Konyndyk DeYoung, 2020-06-02 Drawing on centuries of wisdom from the Christian ethical tradition, this book takes readers on a journey of self-examination, exploring why our hearts are captivated by glittery but false substitutes for true human goodness and happiness. The first edition sold 35,000 copies and was a C. S. Lewis Book Prize award winner. Now updated and revised throughout, the second edition includes a new chapter on grace and growth through the spiritual disciplines. Questions for discussion and study are included at the end of each chapter. |
| ethical guidelines for statistical practice: Managing Applied Social Research Darlene F. Russ-Eft, Catherine M. Sleezer, Gregory Sampson Gruener, Laura C. Leviton, 2017-09-20 Essential management guidance for real-world applied research projects Managing Applied Social Research equips you with the skills, strategies, and knowledge you need to effectively manage research projects. Written by a team of nationally-known researchers, this book covers the systematic management of applied social research studies from 'soup to nuts,' providing researchers with an easy-to-follow process and the tools and templates for improving the quality, ethical conduct, and usefulness of the final products. The authors merge expertise adapted from the field of project management with their decades of experience in using established research methodologies and practices to offer readers; practical examples and insights gleaned from major research houses such as Rand, Urban Institute, Mathematica, American Institutes for Research, and others. Key concepts and methodologies are systematically unpacked, with detailed discussion of both theoretical bases and practical applications in the field. Written in plain English, the case studies and vignettes illustrate typical approaches to different scenarios, and the checklists, templates, and other tools provide guides for action. Starting from basic social research strategies, you'll build an understanding of applied research issues and how projects are best managed in a messy, imperfect world. From conceptualization and proposal through implementation, analysis, and reporting, this book helps you lead your projects to success. Learn the skills and concepts necessary to effectively manage applied research projects for the social science disciplines Anticipate and prepare for common challenges and obstacles Understand the various roles and their requisite tasks and responsibilities Learn strategies for making effective decisions about a study's scope, work, schedule, people, budget, and risks during each phase of the research study Social science research is an essential well of information upon which society is run. Proper management is the key to any research project's success, and success becomes more critical in the field given the potential ramifications in terms of policy and its effects on real, everyday people. Managing Applied Social Research provides sound guidance and expert insight with an essential real-world focus. |
| ethical guidelines for statistical practice: Haschek and Rousseaux's Handbook of Toxicologic Pathology, Volume 1: Principles and Practice of Toxicologic Pathology Wanda M. Haschek, Colin G. Rousseaux, Matthew A. Wallig, Brad Bolon, 2021-10-20 Haschek and Rousseaux's Handbook of Toxicologic Pathology, recognized by many as the most authoritative single source of information in the field of toxicologic pathology, has been extensively updated to continue its comprehensive and timely coverage. The fourth edition has been expanded to four separate volumes due to an explosion of information in this field requiring new and updated chapters. Completely revised with a number of new chapters, Volume 1, Principles and the Practice of Toxicologic Pathology, covers the practice of toxicologic pathology in three parts: Principles of Toxicologic Pathology, Methods in Toxicologic Pathology, and the Practice of Toxicologic Pathology. Other volumes in this work round out the depth and breadth of coverage.Volume 2 encompasses Toxicologic Pathology in Safety Assessment and Environmental Toxicologic Pathology. These two sections cover the application of toxicologic pathology in developing specific product classes, principles of data interpretation for safety assessment, and toxicologic pathology of major classes of environmental toxicants. Volumes 3 and 4 provide deep and broad treatment of Target Organ Toxicity, emphasizing the comparative and correlative aspects of normal biology and toxicant-induced dysfunction, principal methods for toxicologic pathology evaluation, and major mechanisms of toxicity. These volumes comprise the most authoritative reference on toxicologic pathology for pathologists, toxicologists, research scientists, and regulators studying and making decisions on drugs, biologics, medical devices, and other chemicals, including agrochemicals and environmental contaminants. Each volume is being published separately. - Provides new chapters on digital pathology, juvenile pathology, in vitro/in vivo correlation, big data technologies and in-depth discussion of timely topics in the area of toxicologic pathology - Offers high-quality and trusted content in a multi-contributed work written by leading international authorities in all areas of toxicologic pathology - Features hundreds of full-color images in both the print and electronic versions of the book to highlight difficult concepts with clear illustrations |
| ethical guidelines for statistical practice: Intelligent Systems João Carlos Xavier-Junior, Ricardo Araújo Rios, 2022-11-18 The two-volume set LNAI 13653 and 13654 constitutes the refereed proceedings of the 11th Brazilian Conference on Intelligent Systems, BRACIS 2022, which took place in Campinas, Brazil, in November/December 2022. The 89 papers presented in the proceedings were carefully reviewed and selected from 225 submissions. The conference deals with theoretical aspects and applications of artificial and computational intelligence. |
| ethical guidelines for statistical practice: Handbook of Ethics in Quantitative Methodology A. T. Panter, Sonya K. Sterba, 2011-03-01 This comprehensive Handbook is the first to provide a practical, interdisciplinary review of ethical issues as they relate to quantitative methodology including how to present evidence for reliability and validity, what comprises an adequate tested population, and what constitutes scientific knowledge for eliminating biases. The book uses an ethical framework that emphasizes the human cost of quantitative decision making to help researchers understand the specific implications of their choices. The order of the Handbook chapters parallels the chronology of the research process: determining the research design and data collection; data analysis; and communicating findings. Each chapter: Explores the ethics of a particular topic Identifies prevailing methodological issues Reviews strategies and approaches for handling such issues and their ethical implications Provides one or more case examples Outlines plausible approaches to the issue including best-practice solutions. Part 1 presents ethical frameworks that cross-cut design, analysis, and modeling in the behavioral sciences. Part 2 focuses on ideas for disseminating ethical training in statistics courses. Part 3 considers the ethical aspects of selecting measurement instruments and sample size planning and explores issues related to high stakes testing, the defensibility of experimental vs. quasi-experimental research designs, and ethics in program evaluation. Decision points that shape a researchers’ approach to data analysis are examined in Part 4 – when and why analysts need to account for how the sample was selected, how to evaluate tradeoffs of hypothesis-testing vs. estimation, and how to handle missing data. Ethical issues that arise when using techniques such as factor analysis or multilevel modeling and when making causal inferences are also explored. The book concludes with ethical aspects of reporting meta-analyses, of cross-disciplinary statistical reform, and of the publication process. This Handbook appeals to researchers and practitioners in psychology, human development, family studies, health, education, sociology, social work, political science, and business/marketing. This book is also a valuable supplement for quantitative methods courses required of all graduate students in these fields. |
| ethical guidelines for statistical practice: Situated Ethics in Educational Research Helen Simons, Robin Usher, 2012-11-12 Ethics has traditionally been seen as a set of general principles which can be applied in a range of situations. This book argues that in fact ethical principles must be shaped within different research practices and hence take on different significances according to varying research situations. The book develops the notion of situated ethics and explores how ethical issues are practically handled by educational researchers in the field. Contributors present theoretical models and practical examples of what situated ethics involves in conducting research on specific areas. |
| ethical guidelines for statistical practice: Ethics and Data Science Mike Loukides, Hilary Mason, DJ Patil, 2018-07-25 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. |
| ethical guidelines for statistical practice: Research Ethics for Social Scientists Mark Israel, Iain Hay, 2006-06-29 Introduces students to ethical theory and philosophy. This work provides practical guidance on what ethical theory means for research practice; and, offers case studies to give real examples of ethics in research action. |
| ethical guidelines for statistical practice: A Gift of Fire Sara Baase, 2013 This timely revision will feature the latest Internet issues and provide an updated comprehensive look at social and ethical issues in computing from a computer science perspective. |
| ethical guidelines for statistical practice: The Ethics of Biomedical Big Data Brent Daniel Mittelstadt, Luciano Floridi, 2016-08-03 This book presents cutting edge research on the new ethical challenges posed by biomedical Big Data technologies and practices. ‘Biomedical Big Data’ refers to the analysis of aggregated, very large datasets to improve medical knowledge and clinical care. The book describes the ethical problems posed by aggregation of biomedical datasets and re-use/re-purposing of data, in areas such as privacy, consent, professionalism, power relationships, and ethical governance of Big Data platforms. Approaches and methods are discussed that can be used to address these problems to achieve the appropriate balance between the social goods of biomedical Big Data research and the safety and privacy of individuals. Seventeen original contributions analyse the ethical, social and related policy implications of the analysis and curation of biomedical Big Data, written by leading experts in the areas of biomedical research, medical and technology ethics, privacy, governance and data protection. The book advances our understanding of the ethical conundrums posed by biomedical Big Data, and shows how practitioners and policy-makers can address these issues going forward. |
ETHICAL Definition & Meaning - Merriam-Webster
The meaning of ETHICAL is of or relating to ethics. How to use ethical in a sentence. Synonym Discussion of Ethical.
ETHICAL | English meaning - Cambridge Dictionary
ETHICAL definition: 1. relating to beliefs about what is morally right and wrong: 2. morally right: 3. An ethical…. Learn more.
ETHICAL Definition & Meaning | Dictionary.com
Ethical definition: pertaining to or dealing with morals or the principles of morality; pertaining to right and wrong in conduct.. See examples of ETHICAL used in a sentence.
Ethics | Definition, History, Examples, Types, Philosophy, & Facts ...
Apr 21, 2025 · The term ethics may refer to the philosophical study of the concepts of moral right and wrong and moral good and bad, to any philosophical theory of what is morally right and …
Ethical - definition of ethical by The Free Dictionary
1. pertaining to or dealing with morals or the principles of morality; pertaining to ethics. 2. being in accordance with the rules or standards for right conduct or practice, esp. the standards of a …
ethical adjective - Definition, pictures, pronunciation and usage …
Definition of ethical adjective in Oxford Advanced Learner's Dictionary. Meaning, pronunciation, picture, example sentences, grammar, usage notes, synonyms and more.
What does Ethical mean? - Definitions.net
Ethical refers to principles of right or wrong that govern a person's behavior or the conducting of an activity. It pertains to accepted standards of conduct based on concepts of morality, fairness, …
What Does Ethical Mean? | Clear Principles Explained
Ethical refers to principles that govern behavior, ensuring actions align with moral values and societal norms. Ethics is a branch of philosophy that deals with questions about what is morally …
ethical - Wiktionary, the free dictionary
May 15, 2025 · ethical (comparative more ethical, superlative most ethical) (philosophy, not comparable) Of or relating to the study of ethics. The philosopher Kant is particularly known for …
What Does Ethical Mean? - The Word Counter
Apr 2, 2022 · According to Dictionary, the word ethical is an adjective that means related to morals or principles or the concept of right and wrong. If something is ethical, it is within moral rules or …
ETHICAL Definition & Meaning - Merriam-Webster
The meaning of ETHICAL is of or relating to ethics. How to use ethical in a sentence. Synonym Discussion of Ethical.
ETHICAL | English meaning - Cambridge Dictionary
ETHICAL definition: 1. relating to beliefs about what is morally right and wrong: 2. morally right: 3. An ethical…. Learn more.
ETHICAL Definition & Meaning | Dictionary.com
Ethical definition: pertaining to or dealing with morals or the principles of morality; pertaining to right and wrong in conduct.. See examples of ETHICAL used in a sentence.
Ethics | Definition, History, Examples, Types, Philosophy, & Facts ...
Apr 21, 2025 · The term ethics may refer to the philosophical study of the concepts of moral right and wrong and moral good and bad, to any philosophical theory of what is morally right and …
Ethical - definition of ethical by The Free Dictionary
1. pertaining to or dealing with morals or the principles of morality; pertaining to ethics. 2. being in accordance with the rules or standards for right conduct or practice, esp. the standards of a …
ethical adjective - Definition, pictures, pronunciation and usage …
Definition of ethical adjective in Oxford Advanced Learner's Dictionary. Meaning, pronunciation, picture, example sentences, grammar, usage notes, synonyms and more.
What does Ethical mean? - Definitions.net
Ethical refers to principles of right or wrong that govern a person's behavior or the conducting of an activity. It pertains to accepted standards of conduct based on concepts of morality, fairness, …
What Does Ethical Mean? | Clear Principles Explained
Ethical refers to principles that govern behavior, ensuring actions align with moral values and societal norms. Ethics is a branch of philosophy that deals with questions about what is morally …
ethical - Wiktionary, the free dictionary
May 15, 2025 · ethical (comparative more ethical, superlative most ethical) (philosophy, not comparable) Of or relating to the study of ethics. The philosopher Kant is particularly known for …
What Does Ethical Mean? - The Word Counter
Apr 2, 2022 · According to Dictionary, the word ethical is an adjective that means related to morals or principles or the concept of right and wrong. If something is ethical, it is within moral rules or …
