For our August event, we are excited to host Professor Di Cook of Monash University who will be presenting strategies for making plots to explore data using R. There is an interactive component to her talk, and she has requested that attendees download packages tidyverse, plotly, forcats, and nullabor from CRAN, as well as yowie from Github using remotes::install_github(“numbats/yowie”).
This event will be hosted over Zoom, and the link will be available on this Meetup page at noon on the day of the event.
Agenda (times approximate): 7-7:05 pm: R-Ladies NYC Announcements 7:05-7:50: “Making plots to explore data using R” 7:50-8:15: Questions and wrap-up
— Talk Abstract —
Abstract: A recent article by Hullman and Gelman appeared in the Harvard Data Science Review (https://hdsr.mitpress.mit.edu/pub/w075glo6) arguing the need for more theoretical work to support interactive exploratory graphics. It is accompanied by six short informative commentaries. Plots have always been an instrument for data exploration, and yet it is a difficult task, to teach and to conduct. Here we will give a walk-through on organizing your work to make plots to explore data and to quantitatively check if what you see is spurious or special.
— Bio —
Bio: Dianne Cook is Professor of Business Analytics at Monash University in Melbourne, Australia. Her research is in the area of data visualization, especially the visualization of high-dimensional data using tours with low-dimensional projections, and projection pursuit. A current focus is on bridging the gap between exploratory graphics and statistical inference. Di utilizes technology such as virtual environments, Amazon’s Mechanical Turk, and eye-tracking in her work, and makes an effort to share her work with open-source software. Di is a Fellow of the American Statistical Association, elected member of the International Statistical Institute, past-editor of the Journal of Computational and Graphical Statistics, elected Member of the R Foundation, and current editor of the R Journal.