[UPDATE] Thank you for your interest. This workshop is now fully booked out. Please put your name on the waiting list in case for cancellations. We will likely re-run this workshop in the week beginning 13th April 2021 (details to come). We will notify those on the waiting list when this workshop next becomes available.
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Statistical Society of Australia warmly invites you to a workshop on data visualisation with R, taught by Prof. Di Cook and Dr. Emi Tanaka.
This is a repeat of the July workshop. Please note there may be slight changes based on past participant feedback.
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 (on Day 1) will teach you how to create production-ready graphics using the grammar of graphics implemented in ggplot2 R-package. In addition, the workshop (on Day 2) 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 focussing 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:
Day 1 is suitable for those who know R but are not familiar or comfortable with using ggplot2 or would like a refresher on ggplot2.
Day 2 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:
Day 1: Dipping Your Toes into Data Visualization with R
Presented by Emi Tanaka
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Review of tidy data format
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Basics of the grammar of graphics
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Drawing the basic data plot types (barchart, pie chart, histogram, density plot, scatterplot, boxplot) utilising a range of common geoms and variable mappings
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Choosing colour wisely
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All about scales, transforming data, setting limits, changing coordinate systems, axis specifications, ordering levels of categorical axes
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Jazzing up your plot with different themes, plot annotations and combining plots together to make a publication-ready plot
Day 2: Diving Deeper into Data Visualization with R
Presented by Di Cook
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Check your knowledge, a review of basic plotting with the grammar
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Expanding your graphics toolbox to mapping, making choropleth maps, using map images as a base
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Making your plots speak. Adding interactive elements including mouse-over labels, and sliders for controlling parameters, using plotly. Animating plots using gganimate.
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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:
Day 1
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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)
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basic statistics (e.g. simple linear regression, hypothesis testing, basic summary statistics and plots)
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computer (with ability to install R and R-packages), microphone and web camera
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stable internet connection
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Install the video conferencing software, zoom and know how to use zoom
Day 2:
Desirable:
Timetable
Please note that we may modify the schedule slightly after feedback from our July workshop.
Day 1
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1:30pm – 3.00pm (1.5 hours)
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Session 1
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3.00pm – 3.30pm
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Break / networking over virtual morning tea
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3.30pm – 5:00pm (1.5 hours)
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Session 2
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12:30pm
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End of first day
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Day 2
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1.30pm – 3.00pm (1.5 hours)
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Session 1
|
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3.00pm – 3:30pm
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Break / networking over virtual morning tea
|
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3:30pm – 5:00pm (1.5 hours)
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Session 2
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5:00pm
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End workshop
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Deadlines: Early Bird registration closes on 22 Sep
2020. Regular registrations close on midnight on 3 Nov
2020.
Expenses:
Occasionally workshops have to be cancelled due to a lack of subscription. Early registration ensures that this will not happen. Please note that the Society will not be held responsible for any financial loss incurred due to a workshop cancellation.
Financial Support:
Financial support for SSA Vic members can be sought. For further information, please see: https://sites.google.com/view/ssavicworkshopfinsup.
Cancellation policy:
Cancellations received prior to 20 Oct 2020 will be refunded, minus a $20 administration fee. From then onwards 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..
Contact:
Please contact the organisers: Rheanna Mainzer (rheanna.mainzer@gmail.com), Lidija Turkovic (lidijat@gmail.com), and Emi Tanaka (dr.emi.tanaka@gmail.com) for further details.
@StatSocAus
