SSA SCV Tutorial: Creating data plots for effective decision-making using statistical inference with R

Website: https://StatSocAus.github.io/tutorial_effective_data_plots

This is for statisticians and data science practitioners who are interested in improving their data visualisation skills.

Presenter: 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.

Structure of tutorial

• 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.

Course Schedule

time	topic
1:00-1:15	Why, philosophy and benefits
1:15-1:35	Organising data to map variables to plots
1:35-2:05	Making a variety of plots
2:05-2:30	Do but don’t, and cognitive principles
2:30-3:00	BREAK
3:00-3:20	What is your plot testing?
3:20-3:35	Creating null samples
3:35-4:00	Conducting a lineup test
4:00-4:30	Testing for best plot design

Session 1 Slides

Session 2 Slides

Zip file of materials

Getting started

1. You should have a reasonably up to date version of R and R Studio, eg RStudio RStudio 2023.06.2 +561 and R version 4.3.1 (2023-06-16). Install the following packages, and their dependencies.

install.packages(c("ggplot2", "tidyr", "dplyr", "readr", "stringr", "nullabor", "colorspace", "palmerpenguins", "broom", "ggbeeswarm"), dependencies=c("Depends", "Imports"))

2. Download the Zip file of materials to your laptop, and unzip it.

3. Download just the R scripts, slides1.R, slides2.R

4. Open your RStudio be clicking on tutorial.Rproj.

GitHub repo with all materials is https://statsocaus.github.io/tutorial_effective_data_plots/.