Name: Big Data Hubris: Limitations in Aggregating Uber and Google Data
Start: 2020-03-17T18:00:00-04:00
End: 2020-03-17T19:30:00-04:00
Location: Online only

Join us for another joint meeting with West Michigan R User Group (https://westmichiganrusergroup.github.io/about/).

In light of the public-health situation, this meeting will be held via WebEx. This is our first time using this technology to host our meeting, so please bear with us as we experiment and adapt together.

Join by clicking on the link below. If you’re not familiar with WebEx, it would be good to try joining early to get things setup. Note there is an audio only phone line if all you want to do is listen in. Within the WebEx environment we will be able to share video, computer screen, post comments and chat.

JOIN WEBEX MEETING
https://dwz-83.my.webex.com/dwz-83.my/j.php?MTID=m6c986929101edb19bc2ad861fdf82256

Meeting number (access code): 794 328 892

JOIN BY PHONE
+1-408-418-9388 United States Toll

Thomas Weinandy, Ph.D. Candidate at Western Michigan University, will present a talk entitled "Big Data Hubris: Limitations in Aggregating Uber and Google Data." For details, see the Abstract and Bio below.

In addition, a Lightning Talk on "Migrating CRAN Packages After R Upgrades" will be presented by Paul Egeler, M.S., GStat, Spectrum Health Office of Research and Education, This will be an interactive dialogue on how to best migrate packages from previous versions of R into the new R environment after a system upgrade. Paul will discuss common strategies found online as well as his own approach.

Abstract:

Big data hubris is the belief that big data sets are a substitute for, rather than a supplement to, traditional data collection and analysis. Thomas will share how his understanding of big data has evolved during his economics research and why 273 million Uber trips is not considered “big” enough. He will also discuss lessons learned from the rise and fall of Google Flu Trends.

Speaker Bio:

Thomas Weinandy is a Ph.D. Candidate in Applied Economics at Western Michigan University specializing in data analytics and consumer behavior for industrial settings.

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Big Data Hubris: Limitations in Aggregating Uber and Google Data

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Big Data Hubris: Limitations in Aggregating Uber and Google Data

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