Online Program

Tools for Exploratory Data Analysis (303516)

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Keywords: Visualization, Clustering, Dimensionality Reduction, Smoothing

Exploratory data analysis (EDA) is an important step in the data analytic process. We should always first explore our data from different viewpoints, seeking information about relationships and structure that can inform our analysis. In this talk, I will give an overview of several EDA tasks, including visualization, clustering, smoothing, dimensionality reduction, and data tours. However, the main focus of my talk is on the tools one has to conduct EDA. So, I will be providing examples and information about tools and resources data scientists have to utilize the methods. The main goal of this presentation is to help the audience learn about these methods and to provide the means for attendees to use the ideas in their own statistical analyses. Therefore, I will be focusing on open-source tools to make the content available to a wide audience. Examples include R Shiny, GGobi, and open-source executable MATLAB.