c(person("Steph", "Locke", email = "stephanie.g.locke@gmail.com", role = c( "cre","aut")),
person("Alberto", "Cairo", email = "alberto.cairo@gmail.com", role = c( "dtc")),
person("Justin", "Matejka", email = "Justin.Matejka@autodesk.com", role = c( "dtc")),
person("George", "Fitzmaurice", email = "George.Fitzmaurice@autodesk.com", role = c( "dtc")),
person("Lucy", "D'Agostino McGowan", email = "ld.mcgowan@vanderbilt.edu", role = c("aut")),
person("Richard", "Cotton", email = "richierocks@gmail.com", role = c("ctb")),
person("Locke Data", role = c("fnd"))
)
The Datasaurus Dozen is a set of datasets with the same summary statistics. They
retain the same summary statistics despite having radically different distributions.
The datasets represent a larger and quirkier object lesson that is typically taught
via Anscombe's Quartet (available in the 'datasets' package). Anscombe's Quartet
contains four very different distributions with the same summary statistics and as
such highlights the value of visualisation in understanding data, over and above
summary statistics. As well as being an engaging variant on the Quartet, the data
is generated in a novel way. The simulated annealing process used to derive datasets
from the original Datasaurus is detailed in "Same Stats, Different Graphs: Generating
Datasets with Varied Appearance and Identical Statistics through Simulated Annealing"
<doi:10.1145/3025453.3025912>.
covr, testthat, knitr, rmarkdown, ggplot2, dplyr
Steph Locke [cre, aut],
Alberto Cairo [dtc],
Justin Matejka [dtc],
George Fitzmaurice [dtc],
Lucy D'Agostino McGowan [aut],
Richard Cotton [ctb],
Locke Data [fnd]

c(
person("Rhian", "Davies", , "rhian@jumpingrivers.com", role = c("cre", "aut")),
person("Steph", "Locke", , "stephanie.g.locke@gmail.com", role = "aut"),
person("Alberto", "Cairo", , "alberto.cairo@gmail.com", role = "dtc"),
person("Justin", "Matejka", , "Justin.Matejka@autodesk.com", role = "dtc"),
person("George", "Fitzmaurice", , "George.Fitzmaurice@autodesk.com", role = "dtc"),
person("Lucy", "D'Agostino McGowan", , "ld.mcgowan@vanderbilt.edu", role = "aut"),
person("Richard", "Cotton", , "richierocks@gmail.com", role = "ctb"),
person("Tim", "Book", , "TimothyKBook@gmail.com", role = "ctb"),
person("Jumping Rivers", role = "fnd")
)
The Datasaurus Dozen is a set of datasets with the same
summary statistics. They retain the same summary statistics despite
having radically different distributions.  The datasets represent a
larger and quirkier object lesson that is typically taught via
Anscombe's Quartet (available in the 'datasets' package). Anscombe's
Quartet contains four very different distributions with the same
summary statistics and as such highlights the value of visualisation
in understanding data, over and above summary statistics. As well as
being an engaging variant on the Quartet, the data is generated in a
novel way. The simulated annealing process used to derive datasets
from the original Datasaurus is detailed in "Same Stats, Different
Graphs: Generating Datasets with Varied Appearance and Identical
Statistics through Simulated Annealing" <doi:10.1145/3025453.3025912>.
dplyr, ggplot2, knitr, rmarkdown, testthat
Rhian Davies [cre, aut],
Steph Locke [aut],
Alberto Cairo [dtc],
Justin Matejka [dtc],
George Fitzmaurice [dtc],
Lucy D'Agostino McGowan [aut],
Richard Cotton [ctb],
Tim Book [ctb],
Jumping Rivers [fnd]