What We Know about the Quality of Data Used in Data Science

Details

What We Know about the Quality of Data Used in Data Science

Dr. Stephanie Eckman

Abstract
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The insights we get from data science models are only as good as the data that go into the models. Data can suffer from errors of representation (some cases are missing) and errors of measurement (the values in the data set are wrong). Both can cause problems for data scientists training models. I will discuss common data sources and the errors that we find in them. I will provide ideas on how we can address these errors to improve data science models.

About the Speaker
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Dr. Stephanie Eckman is a Fellow in the Survey Research Division at RTI International. She has a Ph.D. in Survey Statistics & Methodology from the Joint Program in Survey Methodology at the University of Maryland.

She specializes in understanding data quality and the social construction of data.

Agenda
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6:30pm – 7:00pm Networking and Refreshments
7:00pm – 7:10pm Introduction, Announcements
7:10pm – 7:40pm Presentation
7:40pm – 7:55pm Q&A
8:00pm – 8:30pm Data Drinks @Tonic (2036 G St NW)