Julian Parris
Room 306, Statistics Building 1130

Modern statistical software isn’t just a tool to help students analyze data, but through interactive graphics and rich statistical visualization these tools help students learn and engage with core concepts in statistics and data analysis. In this session we will see examples of how to use interactivity of software to aid in the communication of otherwise difficult to grasp concepts in the analysis and visualization of data. Examples will include statistical simulations to demonstrate foundational topics such as the sampling distribution of the mean and outlier influence in regression, how interactivity of a visualization can illuminate the output of unsupervised machine learning algorithms for clustering, and how dynamic and responsive graphics can be used to teach core design principles in effective data visualization. (This talk will mainly feature JMP 13 Pro).