CANCELED: Coderspace at ISR with Paul Schulz and Chen Chen
Paul Schulz (U-M, Population Studies Center)
Chen Chen (U-M, Population Studies Center)
Tuesday, 4/7/2020, 10:00am to 11:30am. ARCHIVED EVENT
Location: ISR-Thompson 1430
Do you write code for research or class?
Do you sometimes get stuck?
Or, do you want to learn how to code but don't know where to start?
Or, do you just prefer to work in a more social environment? Writing code, or "programming," can be a fun but also challenging and lonely enterprise. Hosted by members of the ISR community, our CoderSpaces are there for you to meet other coders, so you can connect and learn from your coder peers. Participation is open to anyone interested in code, computational social science, data science, engineering, etc. We seek to build a casual and inclusive environment where everyone is welcome regardless of their skill or level of expertise. To participate, bring a laptop and some coding work, or just come and hang out, socialize, and assist others.
Paul Schulz is a senior consulting statistician and data scientist for ISR's Population Dynamics and Health Program. He specializes in statistical methods and computing, including hypothesis testing, data analysis and modeling, sampling (including weight creation and adjustment, and power calculation), as well as the use of secure computing enclaves (SRCVDI, Likert cluster, and Flux/Great Lakes). Paul writes code in Stata and SAS for general-purpose desktop computing, and R and Python for selected applications, such as data visualization and web scraping/automation, among other uses.
Chen Chen is a data scientist, programmer, and consultant for ISR's Population Dynamics and Health Program. He specializes in survey methods (with a particular focus on survey statistics, sampling, and weighting), data management, and statistical computing, including large scale simulations of complex samples and statistical modeling using complex and longitudinal survey datasets. Chen is a high-level programmer who specializes in R, Python, and Stata, with a focus on computing in a Linux environment.