The tutorials in this NISS series involve the Top 10 analytics approaches of the key topics that are used in business today! Students and faculty, these are perhaps the top ten most important and practical topics that may not be covered in your program of study. (Review the Overview Presentation about all 10 Sessions).
Ethical Practice of Statistics and Data Science in the Social Sciences
Data science is a discipline at the intersection of computing and statistics – two disciplines with long-standing guidance for ethical practice. The “data science pipeline” comprises six tasks: Planning/Designing; Data collection/munging/wrangling; Analysis (perform or program to perform); Interpretation; Documenting your work; Reporting your results/communication; plus a seventh activity, Engaging in team science/team work. The American Statistical Association (ASA) is in the process of revising its current (2018) Ethical Guidelines for Statistical Practice, which are relevant in every step of the pipeline. To demonstrate this relevance and utility, this workshop introduces two important tools practitioners can use to support ethical decision-making along the pipeline: we will examine ethical reasoning, a 6-step process for decision-making, and stakeholder analysis, which can help identify where ethical challenges might arise. Examples of ethical reasoning will be worked through, to promote engagement with the ethical practice standards of the ASA in statistics and data science.
Attendees will want to access and review a copy of the “Ethical Guidelines for Statistical Practice” which was prepared by the Committee on Professional Ethics of the American Statistical Association and approved by the ASA Board in April 2018. Here is a direct link to this .pdf document.
Rochelle Tractenberg (Georgetown University)
NISS is interested in sharing knowledge. To this end, these tutorials have been geared to provide practical information that you can use tomorrow. Examples, projects and code sharing are a part of these sessions wherever possible.
Participants require a working knowledge of probability distributions, statistical inference, statistical modeling and time series analysis as a prerequisite. Students who do not have this foundation or have not reviewed this material within the past couple of years will struggle with the concepts and methods that build on this foundation.
Select a registration/payment option above the 'Register for this Event' button ($35 for this Data Science Essentials tutorial session, $250 for all 10 Essential Data Science for Business tutorial sessions.
Can't attend this session or any of the previous sessions? Post Session Access to tutorial materials and recording can be obtained for $35 after the event is over. Purchasing all 10 Sessions also will provide you access to all previous session recordings and materials.) NISS Affiliates, (https://www.niss.org/affiliates-list), please send an email to email@example.com.). Notifications: You will recieve an email that comes immediately to let you know you paid. Links to the event will come via email the day before and one hour prior to the actual session.
About the Instructor
Dr. Tractenberg is professor in the Department of Neurology, with secondary appointments in the Departments of Biostatistics, Bioinformatics & Biomathematics and Rehabilitation Medicine at Georgetown University, and a Research Fellow at the National Rehabilitation Hospital in Washington, DC. She is a research methodologist specializing in designs and analyses with "difficult to measure" outcomes in biomedical and educational studies. With PhDs in psychology/cognitive sciences (1997) and measurement, statistics, and evaluation (2009); she also earned a doctoral level certificate in gerontology (2006) and brings over 20 years of experience designing and analyzing experimental research.
Her areas of interest include higher education curriculum development and evaluation; statistical methodology and statistical literacy for effective stewardship of the discipline in PhD students/holders; effective instruction and mentoring in research ethics; neuropsychological assessment; the development and benchmarking of outcomes; experimental design; and longitudinal (latent variable) analytic methods.
She was elected a Fellow of the American Statistical Association in 2016 and a Fellow of the American Association for the Advancement of Science in 2017. She was the Chair (2017-2019) of the American Statistical Association Committee on Professional Ethics, serving as Vice-Chair 2014-2016, and chaired the Working Groups on revising the ASA Ethical Guidelines 2014-2016 and 2018; she co-chairs the working group for 2021. In addition to supporting effective curricula (i.e., where intended and actual learning goals are aligned), her work to bring psychometrically-defined validity to curriculum decisions has supported the first ever evidence that training in research ethics can be sustainable (http://www.mdpi.com/2227-7102/7/1/2).
Prior to coming to Georgetown in 2002, Dr. Tractenberg spent five years at the University of California at San Diego as a biostatistician and scientist within a national consortium of Alzheimer's disease research centers. Dr. Tractenberg was the biostatistical consultant for the General Clinical Research Center 2003-2006 and joined the Neurology Department (primary appointment) in 2006. She established the Collaborative for Research on Outcomes and -Metrics (CROM) in 2008 and directs it; for more information, and summaries of current outcomes and metrics projects, check the CROM page. Most of her research (talks, papers, posters) are uploaded to https://georgetown.academia.edu/rochelletractenberg.