How can we make use of new data sources and data science methods to enhance public statistics?
This course gives an overview of advanced topics in official statistics such as Big Data, machine learning, and microsimulations. The benefits and downsides of using Big Data as a data source for official statistics production are discussed and examples of its use are given, including machine learning applications.
In addition, the course provides insights into microsimulation and gives an overview of the past, the present, and the future state-of-the-art of microsimulation methods and applications within official statistics.
This online course uses a flipped classroom design, which means that you can watch the weekly hour of video lectures according to your own schedule. In the weekly one-hour online meetings you have the chance to discuss the material and hands-on applications with the instructors from destatis and Statistics Netherlands.
Basic R knowledge is required. Having some familiarity with the official statistics system as taught in Walter Radermacher’s BERD Academy workshop series “Statistics for the Public Good” can be helpful.
About the Instructors
While Hanna Brenzel, who leads the department at the Federal Statistical Office, holds a doctorate in economics, Hariolf Merkle, who has a Master’s degree in survey statistics, is a Data Scientist at the Deutsche Bundesbank. Dr. Marco Puts, on the other hand, is a Methodologist and Lead Data Scientist at the Central Statistics Office in Heerlen and a Guest Researcher at Radboud University in Nijmegen. Piet Daas is a Methodologist and Professor of Big Data in Official Statistics at Eindhoven University of Technology, specializing as a Data Scientist.