CPD140 - Data Visualisation with R

Statistical Society of Australia warmly invites you to a workshop on data visualisation with R, taught by Prof. Di Cook and Dr. Emi Tanaka.

About the workshop:

Data visualisation is a key statistical tool for effective communication and to understand aspects of data and models. The statistical language R is used widely for data analysis and visualization, e.g. the BBC Visual and Data Journalism team uses ggplot2 R-package to create production-ready charts. This workshop will teach you how to create production-ready graphics using the grammar of graphics implemented in ggplot2 R-package. In addition, the workshop will teach you how to construct more complex plots, including maps, and discuss inference for statistical graphics to understand if what we see in a plot is really there. The workshop will be hands-on with plenty of practical examples.

About the presenters:

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. 

Emi Tanaka is a Lecturer in Statistics at Monash University and the Vice President of SSA Vic. She is currently working on a statistical theory for conducting inference using data plots and is an early career researcher in multi-level modelling, and experimental design. She is an experienced and enthusiastic R user and instructor, and regularly teaches university courses and workshops to the broader community on data visualisation, including ggplot2.

Target audience:

This workshop is suitable for those who know R but are not familiar or comfortable with using ggplot2 or would like a refresher on ggplot2. It is aimed for those that have familiarity with ggplot2 but would like to delve deeper into advanced plotting techniques, including interactive plots and animating plots, and using plots for inference.

Learning objectives:

Dipping Your Toes into Data Visualization with R

Presented by Emi Tanaka

• Review of tidy data format

• Basics of the grammar of graphics

• Drawing the basic data plot types (barchart, pie chart, histogram, density plot, scatterplot, boxplot) utilising a range of common geoms and variable mappings

• Choosing colour wisely

• All about scales, transforming data, setting limits, changing coordinate systems, axis specifications, ordering levels of categorical axes

• Jazzing up your plot with different themes, plot annotations and combining plots together to make a publication-ready plot

Diving Deeper into Data Visualization with R

Presented by Di Cook

• Check your knowledge, a review of basic plotting with the grammar

• Expanding your graphics toolbox to mapping, making choropleth maps, using map images as a base

• Making your plots speak. Adding interactive elements including mouse-over labels, and sliders for controlling parameters, using plotly. Animating plots using gganimate.

• Learn how to decide on the best plot design for a problem, and how to  determine if what you see is a real structure. 
  

Requirements:

• basic R knowledge (e.g. you have used R to load data, create simple visualisations, perform basic analyses and write simple functions or more specifically, you are familiar with concepts in Cookbook for R by Winston Chang)

• basic statistics (e.g. simple linear regression, hypothesis testing, basic summary statistics and plots)

• computer (with ability to install R and R-packages), microphone and web camera 

• stable internet connection

• Install the video conferencing software, zoom and know how to use zoom

Desirable:

• Know about tidy data (i.e. importing data and putting data into the right format for plotting)

• Some familiarity with tidyverse

TimeTable: 

Cancellation policy:

Cancellations received prior to 1 Dec 2021 will be refunded, minus a $20 administration fee. From then onward no part of the registration fee will be refunded. However, registrations are transferable within the same organisation. Please advise any changes to eo@statsoc.org.au..