CPD173- Creating data plots for effective decision-making using statistical inference with R, presented by Dianne Cook

The Statistical Computing and Data Visualisation Section is now offering tutorials.

Creating data plots for effective decision-making using statistical inference with R, presented by Dianne Cook.

Outline

- Review of making effective plots using ggplot2's grammar of graphics:

- Organising your data to enable mapping variables to graphical elements,

- Common plot descriptions as scripts,

- Do's and don'ts following cognitive perception principles.

- Making decisions and inferential statements based on data plots

- What is your plot testing? Determining the hypothesis based on the type of plot.

- Creating null samples to build lineups for comparison and testing.

- Conducting a lineup test using your friends to determine whether what you see is real or spurious, and to determine the best design for your plot.

Background: Participants should have a good working knowledge of R, and tidy verse, and some experience with ggplot2. Familiarity with the material in R4DS (https://r4ds.hadley.nz) is helpful.

BIO: Dianne Cook is Professor of Business Analytics at Monash University in Melbourne, Australia. She is a world leader in data visualisation, especially the visualisation of high-dimensional data using tours with low-dimensional projections, and projection pursuit. She is currently focusing on bridging the gap between exploratory graphics and statistical inference. Di is a Fellow of the American Statistical Association, past editor of the Journal of Computational and Graphical Statistics, current editor of the R Journal, elected Ordinary Member of the R Foundation, and elected member of the International Statistical Institute.