Learn about experimental design and read open-access articles.
Categories: Big Data, Other, Quantitative, Research, Research Design, Research Skills
Continue ReadingLearn about experimental design and read open-access articles.
Categories: Big Data, Other, Quantitative, Research, Research Design, Research Skills
Continue ReadingAn interview with authors who show how to use statistical techniques to understand pressing social issues.
Categories: Big Data, Data Analysis, Instruction, Quantitative, Research
Continue ReadingEvery summer, the Biocomplexity Institute’s Social and Decision Analytics Division’s Data Science for the Public Good (DSPG) Young Scholars program draws university students from around the country to work together on projects that use computational expertise to address critical social issues faced by local, regional, state or federal governments. The students conduct research at the intersection of […]
Categories: Big Data, Quantitative
Continue ReadingEvery summer, the Biocomplexity Institute’s Social and Decision Analytics Division’s Data Science for the Public Good (DSPG) Young Scholars program draws university students from around the country to work together on projects that use computational expertise to address critical social issues faced by local, regional, state or federal governments. The students conduct research at the intersection of […]
Categories: Big Data, Quantitative, Tools and Resources
Continue ReadingEvery summer, the Biocomplexity Institute’s Social and Decision Analytics Division’s Data Science for the Public Good (DSPG) Young Scholars program draws university students from around the country to work together on projects that use computational expertise to address critical social issues faced by local, regional, state or federal governments. The students conduct research at the […]
Categories: Big Data, Quantitative
Continue ReadingThe beneficial symbiosis between behavioral scientists and digital technologists came a cropper earlier this year when the Cambridge Analytica scandal highlighted the fraught relationship that can arise when ethical concerns are overlooked or ignored. And yet the explosion of data comping from corporate sources (35 zettabytes are expected by 2010) and the burgeoning numbers of […]
Categories: Big Data, SAGE Posts, Video
Continue ReadingThe Economic and Social Research Center hosted the biennial Research Methods Festival at the University of Bath. If you weren’t able to attend in person, enjoy this series of posts. Today’s Festival highlight is from SAGE’s own Katie Metler, the Executive Head of Methods Innovation at SAGE Publishing. She has generously shared her presentation slides: Katie discussed […]
Categories: Big Data, Instruction, Mixed, Opportunities, Other, Qualitative, Quantitative, Research Methods, Teaching, Tools and Resources, Video
Continue ReadingIn this archived webinar, Claudia von Vacano and Geoff Bacon, both at the University of California, Berkeley D-Lab and both instructors for SAGE Campus’s “Introduction to Data Science for Social Scientists” course discuss why data science is important to the social sciences, and what social scientists add to this vibrant conversation in the webinar. This […]
Categories: Big Data, SAGE Posts, Video
Continue ReadingIs the skills gap in the social sciences and challenges with data access limiting the potential for big data to be put to “good” use? In this taped debate from the United Kingdom’s Economic and Social Research Council (ESRC) Festival of Social Science, Katie Metzler, head of methods innovation at SAGE Publishing, moderates a panel […]
Categories: Big Data, Research Ethics, SAGE Posts, Video
Continue ReadingBig data and its impact on society and social policy has remained at the forefront of discussions within the social sciences for several years. But as we advance further into this data driven society, examples of big data having been used to maximize profit and cause harm have made global headlines. Those in favor of […]
Categories: Big Data, SAGE Posts, Video
Continue ReadingThis is a group for anyone interested in big data research who wants to share links of interest on the topic.
There is well – forgotten way of visualization of Big Data usually used by applied mathematicians in natural sciences. In comparison with popular Visual Story Telling,this kind of mathematical visualization assumes an e
The knowledge sharing community on “how to do” research methods processes.
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Date/Time
Date(s) - 01/11/2021 - 02/08/2021
All Day
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Based on Dr. Paul Allison’s book Missing Data, this on-demand seminar covers both the theory and practice of two modern methods for handling missing data: multiple imputation and maximum likelihood.
Many researchers have told us that they would love to take the course but just can’t manage the time or the money to attend the live sessions. Developed over three years, this web-based version is a popular alternative for anyone looking for a more flexible option to learn missing data techniques. It is designed to closely match the in-person version, but with substantial additional material.
The course takes place online in a series of four weekly installments of videos, quizzes, readings, and assignments, and requires about 10 hours/week. You may participate at your own convenience; there are no set times when you are required to be online.
This four-week course can be accessed with any recent web browser on almost any platform, including iPhone, iPad, and Android devices. It consists of 12 modules:
This seminar will begin on Monday, January 11, 2021, and conclude on Monday, February 8, 2021.
All course materials are available 24 hours a day. Materials will be accessible for an additional 2 weeks after the official close on February 8.
The fee of $495 (USD) includes all course materials.
For more information on the event and to register, visit the page here.
Date/Time
Date(s) - 01/28/2021 - 01/30/2021
10:00 am - 5:00 pm
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This seminar focuses on methods for the analysis and interpretation of Regression Discontinuity (RD) designs. It will cover both introductory concepts and recent methodological developments.
The RD design is a non-experimental method that has high internal validity for estimating treatment effects. The design can be used when individuals are assigned to some treatment based entirely on a score—in education, this score is usually referred to as a “pretest score”. This could be any quantitative measure, such as an exam grade, income, age, or cholesterol level. All individuals whose score exceeds a predetermined cutoff are offered the treatment, while all individuals below the cutoff are not offered the treatment. For example, if a scholarship is given only to students who score 90 or more points in an exam, the effect of the scholarship could be analyzed with a RD design.
After treatment, an outcome is measured for all individuals–the “posttest score”–which could either be the same variable as the pretest score or a different measure. The analysis focuses on detecting possible discontinuities in the observed relationship between the pretest score and the outcome of interest at the cutoff, under appropriate continuity or local randomization assumptions.
The event runs from Thursday, January 28, 2021 – Saturday, January 30, 2021.
Each day will follow this schedule:
10:00am-2:00pm ET: Live lecture via Zoom
4:00pm-5:00pm ET: Live “office hour” via Zoom (Thursday and Friday only)
The fee of $895 includes all course materials. PayPal and all major credit cards are accepted.
The event details can be found here.
Date/Time
Date(s) - 10/22/2019
9:00 am - 12:00 pm
Location
Faculty of World Studies
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Celebrating the eighth Global Media and Information Literacy Week (24 – 31 Oct 2019), the UNESCO Chair on Cyberspace and Culture is organizing the “Global Media and Information Literacy Seminar: Media and Information Literate Citizens” on Tuesday, 22 October 2019.
This seminar aims to address the concept of MIL Citizens and how MIL can contribute to improving the levels of information, engagement, and empowerment for all. By highlighting these issues, we can progress towards the objectives of open and pluralistic information systems, promoting sustainable development, inclusion, equality, intercultural dialogue, and safeguarding democracy.
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Speakers:
Professor of Communications, the Dean of Faculty of World Studies at University of Tehran, the Secretary of Supreme Council of the Cultural Revolution, and the director of the UNESCO Chair on Cyberspace & Culture, and Cyberspace Policy Research Center
Secretary General of the Iranian National Commission for UNESCO, and Associate Professor at the Faculty of World Studies, University of Tehran
Head of Department of European Studies and Assistant Professor of Communications at the Faculty of World Studies, University of Tehran, journalist and the Editor in Chief of Hamshahri Online
Assistant Professor of Communications at the Faculty of Social Sciences at University of Tehran, and the executive board member of the UNESCO Chair on Cyberspace & Culture
Multidisciplinary Researcher at the Cyberspaces Research Policy Center at University of Tehran, and the executive board member of the UNESCO Chair on Cyberspace & Culture
Date/Time
Date(s) - 02/19/2019 - 02/20/2019
9:00 am - 5:00 pm
Location
SpringHill Suites San Diego
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Statistical Horizons is hosting a 2-day seminar, taught by Dr. Paul Allison, titled Missing Data. The course will take place in San Diego, California, from February 19-20.
This course will cover the theory and practice of both maximum likelihood and multiple imputation. Maximum likelihood for linear models will be demonstrated with SAS, Stata, and Mplus. Mplus will also be used for maximum likelihood with logistic regression. Multiple imputation will be demonstrated with both SAS and Stata.
Conventional methods for missing data, like listwise deletion or regression imputation, are prone to three serious problems:
Anyone who does statistical analysis can benefit from new methods for handling missing data. To take this course, you should have a good working knowledge of the principles and practice of multiple regression.
This two day course hosted by Statistical Horizons is $995 for two days, which includes all materials. To register for the course CLICK HERE.
Date/Time
Date(s) - 08/09/2018
12:30 pm - 5:00 pm
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Please join the The Social and Decision Analytics Laboratory at Virginia Tech for this summer’s Data Science for the Public Good (DSPG) Symposium where DSPG students and fellows will present their research projects. This symposium will highlight how the DSPG program equips new generations of scientists with the skills they need to develop data-driven policy and decision-making.
The DSPG program focuses at the interface of data analytics and social science to address real problems at the local, state, and federal levels of government. The Symposium will include two keynote speakers followed by a poster session and networking reception.
Keynote Speakers:
• Catherine Woteki, former undersecretary for research, education and economics and chief scientist, U.S. Department of Agriculture
• Wayne Strickland, executive director, Roanoke Valley-Alleghany Regional Commission
If you are an individual with a disability and desire an accommodation, please contact Lori Conerly at loric17@vt.edu during regular business hours at least ten business days prior to the event.
Zoom Information:
Join from PC, Mac, Linux, iOS or Android: https://virginiatech.zoom.us/j/553667234
NOTE: Zoom will open at 12:50 p.m. and the symposium will begin at 1 p.m.
AGENDA:
12:30 p.m. Registration
1 p.m. Welcome & Introductions
Sallie Keller, Director and Professor of Statistics, SDAL
1:15 p.m. Keynote Speakers
1:15-1:45 p.m. Catherine Woteki
1:45-2:15 p.m. Wayne Strickland
2:15–2:30 p.m. Poster Slam – DSPG fellows and students promote their research posters in a fast-paced session and invite the audience to review their posters
2:30–5 p.m. Poster Session & Networking Reception
To register for the free event, CLICK HERE.
SDAL brings together statisticians and social and behavioral scientists to embrace today’s data revolution, developing evidence-based research and quantitative methods to inform policy decision-making.