1. Understanding Gov’t Statistics
Shuming Bao1 and Tao Hu2
1China Data Institute & Future Data Lab
2Center for Geographic Analysis, Harvard University
11:00AM-12:00PM, Thursday, US Eastern Time
September 24, 2020
This webinar will discuss the following topics: (1) data sources, collection, category, definition, description, and interpretation; (2) alternative data for gov’t statistics, especially data derived from big data sources; (3) comparison of the difference between the US and China statistics; (4) discussions of pros and cons; (5) workflow-based data analysis case studies.
About the speakers：
Dr. Shuming Bao is the director of the China Data Institute and Future Data Lab in the US. He was a faculty member and the director of the China Data Center at the University of Michigan in Ann Arbor before he established the China Data Institute.
Dr. Tao Hu is the post-doc fellow of the Center for Geographic Analysis at Harvard University. He received his Ph.D. from Wuhan University. His primary research field is GIScience with a focus on spatiotemporal analysis.
Q: Is this program free?
A: It is FREE for those current China Data Online subscribers, including all staff, faculty, students, affiliates who have a valid email account from those institutions which have a subscription to China Data Online (http://china-data-online.com). Otherwise, there is a registration fee (see details at https://chinadatacenter.net/Learming/SeminarsContent.aspx?id=5114).
Q: Is the registration required to participate in the webinar?
A: Yes. Those who have registered but missed the webinars will receive a link for recorded webinars and PPTs, hosted by RMDS Lab, after each webinar. All registered participants can enjoy the following benefits in addition to the reminder of the data training webinar: (1) access to the recorded webinar and PPT presentation; (2) complementary access to China Statistics Online (http://china-data-onoine.com; (3) complementary ticket for the training webinar on data analysis workflows (see https://www.eventbrite.com/e/121260468325), which is co-sponsored by RMDS Lab and Future Data Lab.
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