R is an open-source programming language and environment with powerful and extensive features for data analysis, data visualization, and statistical computing. Although R first appeared in the 1990s, ...

Area(s) of potential collaboration: Would like to collaborate with faculty who are interested in developing grant proposals that involve GIS and network analytics. Primary research focus: I study how ...

I propose the following law: “The longer an innovative visualization exists, the probability someone says it should have been a line/bar chart approaches 1” I’ve seen the “shoulda been a line chart” ...

The social science data analysis and visualization minor introduces students to the fundamentals and current innovations of research and data analysis across social science disciplines. It equips ...

Topological data analysis (TDA) is a methodology designed to study qualitative properties (shapes) of data using topological, statistical, and computational ideas. This topological framework has ...

Designed to introduce students to quantitative methods in a way that can be applied to all kinds of data in all kinds of situations, Statistics and Data Visualization Using R: The Art and Practice of ...

Recent advances in microarray technology have led to the proliferation of experiments simultaneously measuring the transcriptional responses of massive amounts of genes to a variety of stimuli. The ...

The table below shows my favorite go-to R packages for data import, wrangling, visualization and analysis — plus a few miscellaneous tasks tossed in. The package names in the table are clickable if ...

This second course of the Data-Driven Decision Making (DDDM) series provides a high-level overview of data analysis and visualization tools, preparing learners to discuss best practices and develop an ...

Data visualisation and chart analysis have evolved into essential tools for exploring and communicating complex quantitative information. Modern research within this field focuses on automating the ...

You’ve generated a ton of data. How do you analyze it and present it? Sure, you can use a spreadsheet. Or break out some programming tools. Or try LabPlot. Sure, it is sort of like a spreadsheet. But ...