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I do research in data visualisation, with a statistical focus. This includes visualising high-dimensional spaces using tours with low-dimensional projections, see the tourr. Yes, you can see beyond 3D. My recent work sets up a framework to bridge the long-standing gap between exploratory and confirmatory statistics, with the essential ingredient being to consider a data plot as a statistic, like the mean is a statistic. Thinking about data plots using a grammar of graphics makes this possible. The R package nullabor has functions for conducting inference with plots. Technology plays an important role in data visualisation for evaluating effectiveness and for public consumption. I have experimented with virtual environments, Amazon’s Mechanical Turk, and eye-tracking. Some of my past software projects are xgobi, ggobi, cranvas and a number of R packages. Mostly, I am curious about our world and use data plots to understand what is happening around me.
I am a Fellow of the American Statistical Association, elected Ordinary Member of the R Foundation, elected member of the International Statistical Institute, current editor of the R Journal and past editor of the Journal of Computational and Graphical Statistics. See CV for more details.
Interests
Interactive data visualisation
Exploratory data analysis
High-dimensional spaces
Statistical graphics
Statistical computing
Bioinformatics
Sports
Ecology
Environment
Open source
Open data
Education
PhD in Statistics, 1993
Rutgers University
换ip软伀
Rutgers University
BSc/Dip Ed in Mathematics, Statistics and Biochemistry, 1982
University of New England
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More Publications
Vanderplas, S., Cook, D., Hofmann, H..
Testing Statistical Charts: What Makes a Good Graph?.
In ARSIA,
2022.
Preprint
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Code
换ip软伀
Project
Poster
Slides
Video
Source Document
如何使用换IP软伀修改电脑IP地址-百度经验:2021-11-15 · 如何使用换IP软伀修改电脑IP地址,技术牛的程序员会自己搭建IP企理池，不过对于刚入门的小白或者工作时间很紧凑的人换i软伀更加方便一些。下面就来讲讲如何使用换i软伀.
A new tidy data structure to support exploration and modeling of temporal data.
In JCGS,
2022.
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PDF
Code
Dataset
Project
Poster
Slides
Video
Source Document
Wang, E., Cook, D., Hyndman, R. J..
Calendar-based graphics for visualizing people's daily schedules.
In JCGS,
2022.
Preprint
PDF
Code
Dataset
Project
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Slides
Video
Source Document
Forbes, J., Cook, D., Hyndman, R. J..
Spatial modelling of the two-party preferred vote in Australian federal elections: 2001–2016.
In ANZJS,
2022.
Preprint
PDF
Code
Dataset
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Poster
Slides
Video
Source Document
Rutter, L., Vanderplas, S., Cook, D., Graham, M..
ggenealogy: An R Package for Visualizing Genealogical Data.
In Genome Biology,
2022.
Preprint
PDF
Code
Dataset
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Slides
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Source Document
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More Talks
The paradox of the positive: exploratory tools for visualising the individuals in (multivariate) longitudinal data
Jul 20, 2022
7:00 PM
IBC 2022
Slides
Code
Making inference using data plots, with application to ecological statistics
Jun 24, 2022
7:00 AM
vISEC 2022
Slides
Code
Going beyond 2D and 3D to visualise higher dimensions, for ordination, clustering and other models
Building plots to explore data: Beyond histograms, barcharts and scatterplots to high-dimensions and statistical inference
Aug 23, 2022
9:25 AM
ISI WSC 2022
Slides
Code
Human vs computer: when visualising data, who wins?
Aug 14, 2022
9:00 AM
DSSV 2022
Slides
Code
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More Posts
How to use a tour to check if your model suffers from multicollinearity
Di Cook
4 min read
data visualisation,
statistics
Multicollinearity This was one of the comments from a recent review of a paper:
As you note in the paper, it seems likely that there are still issues with multi-collinearity
Multicollinearity means that the observations are co-linear in some combination of the variables. This has been relaxed in practice to mean substantial association between explanatory variables. When your explanatory variables have substantial association between them, it means that you don’t have a stable base on which to build a model.
Di Cook更改国外ip软伀
data visualisation,
R,
tidyverse,
time series,
smart meter
Download your data You can get access to your own electricity and gas usage data from http://www.citipower.com.au/our-services/myenergy. You will need a copy of your power bill, which has your smart meter number and meter id, to register for an account.
Reading the data The data structure is described here.
The data is not especially nicely formatted (surprise). The main components are:
The time resolution is half-hourly. And values for each day are spread across the columns.
Stuart Lee, Di Cook
7 min read
education,
statistical graphics,
data visualisation,
R,
ggplot2
In this assignment, the focus was to practice data cleaning. Students suggested questions to build a class survey, to get to know the interests of other class members, and then completed the composed survey. After cleaning the data, a few summary plots of interesting aspects of the data were made. There are some common mistakes that rookies often make when constructing data plots: packing too much into a single graphic, leaving categorical variables unordered, reversing norms for response and explanatory variables, conditioning in wrong order, plotting counts when proportions should be the focus, not normalizing by counts, using a boxplot for small sample size.
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All
Research
Conference
WOMBAT 2022
Workshop Organised by the Monash Business Analytics Team, sponsored by the Monash University Network of Excellence on High-Dimensional Dynamic Systems
nullabor
R package containing tools for doing statistical inference with data plots
foRwards
Leading the R community forwards in widening the participation of women and other under-represented groups.
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Non-Uniform Monash Business Analytics Team: This is a research working group consisting of facutly, post-docs and students in Econometrics and Business Statistics at Monash University. The group meets regularly to discuss current research and host visitors talking to the group. If you would like to visit and present your work to the group, send email numbats@googlegroups.com.
useR! 2018
The conference useR! 2018 will be held in Australia July 10-13, at the Brisbane Convention and Exhibition Centre. This is the first time that it has been held outside Europe or North America.
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dicook@monash.edu
+61 (0) 3990 52608
visnut
E762A Menzies, 20 Chancellors Walk, Clayton, Vic, 3800, Australia
By appointment
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EDA
R
Rmd
XML
animation
barcharts
business analytics
chance
community
computational statistics
conference
cranvas
cricket
换ip软伀
data science
data visualisation
data visualization
换ip软伀
diversity
education
facetting
forecasting
ggplot2
inference
interactive graphics
lineups
mosaic plots
multivariate data
nullabor
换ip软伀
plotly
politics
programming languages
research
scatterplot
slides
换ip软伀
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sports statistics
statistical computing
statistical graphics
statistical software
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tidyverse
time series
tour
tours
visual inference
xaringan
