This workshop will cover dimension reduction techniques for data analysis in Python, focusing on Principal Component Analysis (PCA), factor analysis, and canonical correlation analysis (CCA). Depending on audience interest, dimension […]
This lecture-format workshop will present an overview of available modes and methods of survey data collection as well as an introduction to the survey response process and implications for questionnaire […]
This workshop is designed for those who are interested in getting started with their own research and analytics of Twitter data. The workshop introduces workflows for using the Twitter API […]
Simulation studies are used to understand the properties of statistical procedures. This technique is widely used when conducting power analysis for research studies, which is one focus for this workshop. […]
This workshop will cover introductory GIS concepts, tools, and techniques. We will use QGIS (and ArcGIS) and learn the basics of vector- and network-data GIS by solving problems. You will also […]
OVERVIEW This workshop will provide a brief overview of the components of the Great Lakes Cluster. The main body of the workshop will cover the resource manager and scheduler, creating […]
This workshop will cover techniques for conducting large-scale inference, using Python and its libraries. We will cover the principals of how large scale inference is different from classical inference, and […]
OVERVIEW This workshop will cover some more advanced topics in cluster computing on the U-M Great Lakes Cluster. Topics to be covered include a review of common parallel programming models […]
This brief workshop will demonstrate the capabilities of two recent R packages, gganimate and patchwork. One package allows the data explorer to provide some lively enhancement to an otherwise static […]
Topics: By the end of the workshop, participants will be able to: Work with Stata, including using Do-files and using the help system. Get data into Stata and manage your […]