(47) Data Management with R: Become a Data Wrangler
Session Number: 47
Track: Professional Development Workshops
Session Type: Professional Development Workshops
Workshop Lead Presenter: Tony Fujs [Director of Evaluation - LAYC]
Other Workshop Presenter: Kealy Sloan [Learning and Evaluation Specialist - The Latin American Youth Center]
Time: Nov 11, 2015 (12:00 PM - 03:00 PM)
Audience Level: Intermediate
Learning Outcomes: • Learn a theoretical framework to think about data cleaning and be introduced to a step-by-step approach to get from raw data to tidy data
• Use a set of tools and methods to implement this framework, and effectively tackle common data management tasks such as: identifying duplicates, inconsistencies, typos, and outliers, merging datasets, recoding variables, reshaping datasets (long versus wide formats), and dealing with missing values, amongst others
• Identify links between theory and practice: attendees will have the opportunity to exercise their new skills through practical applications and hands-on activities. Additionally, attendees are encouraged to communicate in advance their own raw data sets, or specific data management issues, to the instructor so they can be integrated into the workshop as real world examples
Facilitation Experience: In the past year, Tony Fujs facilitated professional development workshop at institutions such as the Urban Institute, Georgetown University, and the Eastern Evaluation Research Society (EERS), amongst others. He has taught this workshop before for the Latin American Youth Center evaluation team, as well as for the EERS 2015 conference.
As the Director of Learning and Evaluation at the Latin American Youth Center in DC, Mr. Fujs supports information-based decision making, and improves organizational performance. For the past five years, He has been using R to streamline data cleaning and data management, scale analytic, and improve visualizations of LAYC's data.
Session Abstract: The objective of this workshop is to provide attendees with concrete steps and tools to become skillful "data wranglers". Evaluators working with quantitative data spend a lot of time (too much!) addressing data quality issues, and re-arranging their data sets into analytic-friendly formats. Even though this is a critical part of the data analysis process, data management has received limited attention in the social sciences literature. Through a mix of theory, best practices, and hands-on experience with real data-sets, attendees will:
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Cancellation Policy: Refunds less a $50 fee will be granted for requests received in writing prior to 11:59 PM EDT October 6, 2015. Email cancellation requests to firstname.lastname@example.org. Fax request to (202) 367-2173. All refunds are processed after the meeting. After October 6, 2015 all sales are final.