Office of Advanced Research Computing

Part of the Data Topics series of workshops, this workshop reviews statistical tests, regression, sampling and bootstrap methods, and more. The focus here is on implementing statistics using R, with a comparison to Python techniques for accomplishing similar tasks. Supplemental materials are available.

A Geographic Information System (GIS) can be a very useful tool for your research by incorporating location when exploring questions. In this short, interactive workshop, we will cover basic GIS concepts using ArcGIS Online. We'll explore the interface, add and visualize data, run a quick analysis, and create and share a map. Make sure to … Read More

"Everything happens somewhere..." In this short, interactive workshop, learn how spatial data might enhance your research. We'll explore free and proprietary GIS (geographic information systems) data resources, search strategies to uncover available data; adapting public data for use, review critical data literacy and the importance of attribution, and discuss the process of building your own … Read More

The ggplot2 package from the tidyverse provides extensive and flexible graphical capabilities within a consistent framework.  This session introduces the main features of ggplot2. Some prior familiarity with R is assumed (packages, structure, syntax), but the presentation can be followed without this background. Supplemental materials are available.

Create data management and sharing plans that meet funder requirements using DMPTool. Features of this plan writing tool will be demonstrated, with tips for writing plans for NIH and NSF. Information about selecting data repositories will also be presented. There will be time at the end for Q&A - please bring your data management questions!

Creating interactive visualizations with Shiny in RStudio, and delivering Shiny visualizations on the web and hosting a Shiny server. Supplemental materials are available.

This session introduces the R statistical software environment, basic methods of data analysis, and the "tidyverse." While R is much more than the tidyverse, the development of the tidyverse packages, led by RStudio, has provided a powerful and connected toolkit to get started using R. Note that graphics and data manipulation are covered in subsequent … Read More