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vis.bib
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@misc{camoes_stephen_2010,
title = {Stephen {Few}, {Data} {Visualization}, {Eye} {Candy} and {Pie} {Charts}},
url = {http://www.excelcharts.com/blog/stephen-few-data-visualization-eye-candy-and-the-pie/},
urldate = {2010-09-30},
author = {Camoes, Jorge}
}
@article{levine_editorial_2010,
title = {Editorial: {Publishing} {Animations}, 3D {Visualizations}, and {Movies} in {JCGS}},
volume = {19},
issn = {1061-8600, 1537-2715},
shorttitle = {Editorial},
url = {http://amstat.tandfonline.com/doi/abs/10.1198/jcgs.2010.191ed},
doi = {10.1198/jcgs.2010.191ed},
number = {1},
urldate = {2012-05-11},
journal = {Journal of Computational and Graphical Statistics},
author = {Levine, Richard A. and Tierney, Luke and Wickham, Hadley and Sampson, Eric and Cook, Dianne and van Dyk, David A.},
month = jan,
year = {2010},
pages = {1--2}
}
@book{steele_beautiful_2010,
edition = {1},
title = {Beautiful {Visualization}: {Looking} at {Data} through the {Eyes} of {Experts}},
isbn = {1-4493-7986-9},
shorttitle = {Beautiful {Visualization}},
publisher = {O'Reilly Media},
author = {Steele, Julie and Iliinsky, Noah},
month = jun,
year = {2010}
}
@book{sarkar_lattice_2008,
edition = {1},
title = {Lattice: {Multivariate} {Data} {Visualization} with {R}},
isbn = {0-387-75968-9},
shorttitle = {Lattice},
publisher = {Springer},
author = {Sarkar, Deepayan},
month = mar,
year = {2008}
}
@misc{noauthor_data_nodate,
title = {Data visualization: {A} view of every {Points} of {View} column : {Methagora}},
url = {http://blogs.nature.com/methagora/2013/07/data-visualization-points-of-view.html},
urldate = {2015-05-22},
file = {Data visualization\: A view of every Points of View column \: Methagora:/home/bolker/.mozilla/firefox/f2nw6467.default/zotero/storage/24IZIWDV/data-visualization-points-of-view.html:text/html}
}
@article{kahle_ggmap_2013,
title = {ggmap : {Spatial} {Visualization} with ggplot2},
volume = {5},
url = {http://journal.r-project.org/archive/2013-1/RJournal_2013-1_kahle-wickham.pdf},
number = {1},
journal = {The R Journal},
author = {Kahle, David and Wickham, Hadley},
month = jun,
year = {2013},
pages = {144--162}
}
@book{steele_beautiful_2010-1,
title = {Beautiful {Visualization}},
isbn = {978-1-4493-7986-5},
publisher = {O'Reilly Media, Inc.},
author = {Steele, Julie and Iliinsky, Noah},
month = jun,
year = {2010}
}
@book{few_now_2009,
edition = {1st},
title = {Now {You} {See} {It}: {Simple} {Visualization} {Techniques} for {Quantitative} {Analysis}},
isbn = {0-9706019-8-0},
shorttitle = {Now {You} {See} {It}},
publisher = {Analytics Press},
author = {Few, Stephen},
month = apr,
year = {2009}
}
@article{li_judging_2008,
title = {Judging correlation from scatterplots and parallel coordinate plots},
issn = {1473-8716},
url = {http://www.palgrave-journals.com/ivs/journal/vaop/ncurrent/abs/9500179a.html},
doi = {10.1057/palgrave.ivs.9500179},
urldate = {2009-11-11},
journal = {Information Visualization},
author = {Li, Jing and Martens, Jean-Bernard and van Wijk, Jarke J},
month = may,
year = {2008},
file = {Information Visualization - Abstract of article\: Judging correlation from scatterplots and parallel coordinate plots:/home/bolker/.mozilla/firefox/f2nw6467.default/zotero/storage/IPH4KZVV/9500179a.html:text/html}
}
@article{kahle_ggmap_2013-2,
title = {ggmap : {Spatial} {Visualization} with ggplot2},
volume = {5},
url = {http://journal.r-project.org/archive/2013-1/RJournal_2013-1_kahle-wickham.pdf},
number = {1},
journal = {The R Journal},
author = {Kahle, David and Wickham, Hadley},
month = jun,
year = {2013},
pages = {144--162}
}
@article{su_its_2008,
title = {It’s easy to produce chartjunk using {Microsoft}®{Excel} 2007 but hard to make good graphs},
volume = {52},
url = {http://www.sciencedirect.com/science?_ob=ArticleURL&_udi=B6V8V-4S1S6FC-6&_user=10&_rdoc=1&_fmt=&_orig=search&_sort=d&view=c&_acct=C000050221&_version=1&_urlVersion=0&_userid=10&md5=d3e57dcf23c1adccee012110b71fefcf},
doi = {10.1016/j.csda.2008.03.007},
abstract = {The purpose of default settings in a graphic tool is to make it easy to produce good graphics that accord with the principles of statistical graphics, e.g., [Tufte, E.R., 1990. Envisioning Information. Graphics Press, Cheshire, Conn, Tufte, E.R., 1997. Visual Explanations: Images and Quantities, Evidence and Narrative, 2nd Edition. Graphics Press, Cheshire, Conn, Cleveland, W.S., 1993. Visualizing Data. Hobart Press, N.J Cleveland, W.S., 1994. The Elements of Graphing Data, rev. edition. AT\&T Bell Laboratories, Murray Hill, N.J, Wainer, H., 1997. Visual revelations: Graphical tales of fate and deception from Napoleon to Ross Perot. Copernicus, New York, Spence, R., 2001. Information Visualization. ACM Press \& AddisonWesley, New York, and Few, S., 2004. Show Me the Numbers. Analytic Press, Hillsdale, NJ]. If the defaults do not embody these principles, then the only way to produce good graphics is to be sufficiently familiar with the principles of statistical graphics. This paper shows that Excel graphics defaults do not embody the appropriate principles. Users who want to use Excel are advised to know the principles of good graphics well enough so that they can choose the appropriate options to override the defaults. Microsoft® should overhaul the Excel graphics engine so that its defaults embody the principles of statistical graphics and make it easy for non-experts to produce good graphs.},
number = {10},
urldate = {2008-07-04},
journal = {Computational Statistics \& Data Analysis},
author = {Su, Yu-Sung},
month = jun,
year = {2008},
pages = {4594--4601},
file = {ScienceDirect Snapshot:/home/bolker/.mozilla/firefox/f2nw6467.default/zotero/storage/T6N4TMUQ/science.html:text/html}
}
@article{gelman_infovis_2013,
title = {Infovis and {Statistical} {Graphics}: {Different} {Goals}, {Different} {Looks}},
volume = {22},
issn = {1061-8600},
shorttitle = {Infovis and {Statistical} {Graphics}},
url = {http://www.tandfonline.com/doi/abs/10.1080/10618600.2012.761137},
doi = {10.1080/10618600.2012.761137},
abstract = {The importance of graphical displays in statistical practice has been recognized sporadically in the statistical literature over the past century, with wider awareness following Tukey's Exploratory Data Analysis and Tufte's books in the succeeding decades. But statistical graphics still occupy an awkward in-between position: within statistics, exploratory and graphical methods represent a minor subfield and are not well integrated with larger themes of modeling and inference. Outside of statistics, infographics (also called information visualization or Infovis) are huge, but their purveyors and enthusiasts appear largely to be uninterested in statistical principles. We present here a set of goals for graphical displays discussed primarily from the statistical point of view and discuss some inherent contradictions in these goals that may be impeding communication between the fields of statistics and Infovis. One of our constructive suggestions, to Infovis practitioners and statisticians alike, is to try not to cram into a single graph what can be better displayed in two or more. We recognize that we offer only one perspective and intend this article to be a starting point for a wide-ranging discussion among graphic designers, statisticians, and users of statistical methods. The purpose of this article is not to criticize but to explore the different goals that lead researchers in different fields to value different aspects of data visualization.},
number = {1},
urldate = {2013-07-01},
journal = {Journal of Computational and Graphical Statistics},
author = {Gelman, Andrew and Unwin, Antony},
year = {2013},
pages = {2--28},
file = {Full Text PDF:/home/bolker/.mozilla/firefox/f2nw6467.default/zotero/storage/FPZGWWSB/Gelman and Unwin - 2013 - Infovis and Statistical Graphics Different Goals,.pdf:application/pdf;Snapshot:/home/bolker/.mozilla/firefox/f2nw6467.default/zotero/storage/JD3PKJ4X/10618600.2012.html:text/html}
}
@article{thompson_graphical_2010,
title = {Graphical {Comparison} of {MCMC} {Performance}},
url = {http://arxiv.org/abs/1011.4457},
abstract = {This paper presents a graphical method for comparing performance of Markov Chain Monte Carlo methods. Most researchers present comparisons of MCMC methods using tables of figures of merit; this paper presents a graphical alternative. It first discusses the computation of autocorrelation time, then uses this to construct a figure of merit, log density function evaluations per independent observation. Then, it demonstrates how one can plot this figure of merit against a tuning parameter in a grid of plots where columns represent sampling methods and rows represent distributions. This type of visualization makes it possible to convey a greater depth of information without overwhelming the user with numbers, allowing researchers to put their contributions into a broader context than is possible with a textual presentation.},
urldate = {2010-11-22},
journal = {1011.4457},
author = {Thompson, Madeleine B},
month = nov,
year = {2010},
keywords = {Statistics - Computation, G.3},
file = {1011.4457 PDF:/home/bolker/.mozilla/firefox/f2nw6467.default/zotero/storage/VHPNUKD5/Thompson - 2010 - Graphical Comparison of MCMC Performance.pdf:application/pdf;arXiv.org Snapshot:/home/bolker/.mozilla/firefox/f2nw6467.default/zotero/storage/Q2R69HTJ/1011.html:text/html}
}
@article{peltonen_visualizations_2009,
title = {Visualizations for assessing convergence and mixing of {Markov} chain {Monte} {Carlo} simulations},
volume = {53},
issn = {01679473},
url = {http://linkinghub.elsevier.com/retrieve/pii/S0167947309002461},
doi = {10.1016/j.csda.2009.07.001},
number = {12},
journal = {Computational Statistics \& Data Analysis},
author = {Peltonen, Jaakko and Venna, Jarkko and Kaski, Samuel},
month = oct,
year = {2009},
pages = {4453--4470}
}
@article{wickham_graphical_2010,
title = {Graphical inference for infovis},
volume = {16},
issn = {1077-2626},
doi = {10.1109/TVCG.2010.161},
abstract = {How do we know if what we see is really there? When visualizing data, how do we avoid falling into the trap of apophenia where we see patterns in random noise? Traditionally, infovis has been concerned with discovering new relationships, and statistics with preventing spurious relationships from being reported. We pull these opposing poles closer with two new techniques for rigorous statistical inference of visual discoveries. The "Rorschach" helps the analyst calibrate their understanding of uncertainty and "line-up" provides a protocol for assessing the significance of visual discoveries, protecting against the discovery of spurious structure.},
number = {6},
journal = {IEEE Transactions on Visualization and Computer Graphics},
author = {Wickham, H. and Cook, D. and Hofmann, H. and Buja, Andreas},
month = nov,
year = {2010},
keywords = {Testing, Models, Statistical, Neoplasms, null hypotheses, Computer Graphics, infovis, data visualization, visual testing, Protocols, Accuracy, data visualisation, Humans, Databases, Factual, Histograms, data plot, Data Interpretation, Statistical, graphical inference, Tag clouds, statistics, permutation tests, Visualization, Statistical inference},
pages = {973--979},
file = {IEEE Xplore Abstract Record:/home/bolker/.mozilla/firefox/f2nw6467.default/zotero/storage/6U3IB5QM/abs_all.html:text/html;Wickham et al_2010_Graphical inference for infovis.pdf:/home/bolker/.mozilla/firefox/f2nw6467.default/zotero/storage/KGAEDMF8/Wickham et al_2010_Graphical inference for infovis.pdf:application/pdf}
}
@article{friendly_effect_2003,
series = {Data {Visualization}},
title = {Effect ordering for data displays},
volume = {43},
issn = {0167-9473},
url = {http://www.sciencedirect.com/science/article/pii/S0167947302002906},
doi = {10.1016/S0167-9473(02)00290-6},
abstract = {This paper outlines a general framework for ordering information in visual displays (tables and graphs) according to the effects or trends which we desire to see. This idea, termed effect-ordered data displays, applies principally to the arrangement of unordered factors for quantitative data and frequency data, and to the arrangement of variables and observations in multivariate displays (star plots, parallel coordinate plots, and so forth).
As examples of this principle, we present several techniques for ordering items, levels or variables “optimally”, based on some desired criterion. All of these may be based on eigenvalue or singular-value decompositions.
Along the way, we tell some stories about data display, illustrated by graphs—some surprisingly bad, and some surprisingly good—for showing patterns, trends, and anomalies in data. We hope to raise more questions than we can provide answers for.},
number = {4},
urldate = {2016-01-23},
journal = {Computational Statistics \& Data Analysis},
author = {Friendly, Michael and Kwan, Ernest},
month = aug,
year = {2003},
pages = {509--539},
file = {ScienceDirect Snapshot:/home/bolker/.mozilla/firefox/f2nw6467.default/zotero/storage/C79AU4QH/S0167947302002906.html:text/html}
}
@misc{machlis_best_2015,
title = {Best {R} packages for data import, data wrangling \& data visualization},
url = {http://www.computerworld.com/article/2921176/business-intelligence/great-r-packages-for-data-import-wrangling-visualization.html},
abstract = {Useful R packages in a handy searchable table},
urldate = {2016-05-16},
journal = {Computerworld},
author = {Machlis, Sharon},
month = nov,
year = {2015},
file = {Snapshot:/home/bolker/.mozilla/firefox/f2nw6467.default/zotero/storage/8B6B4ZUG/great-r-packages-for-data-import-wrangling-visualization.html:text/html}
}
@article{zuur_protocol_2016,
title = {A protocol for conducting and presenting results of regression-type analyses},
volume = {7},
issn = {2041-210X},
url = {http://onlinelibrary.wiley.com/doi/10.1111/2041-210X.12577/abstract},
doi = {10.1111/2041-210X.12577},
abstract = {* Scientific investigation is of value only insofar as relevant results are obtained and communicated, a task that requires organizing, evaluating, analysing and unambiguously communicating the significance of data. In this context, working with ecological data, reflecting the complexities and interactions of the natural world, can be a challenge. Recent innovations for statistical analysis of multifaceted interrelated data make obtaining more accurate and meaningful results possible, but key decisions of the analyses to use, and which components to present in a scientific paper or report, may be overwhelming.
* We offer a 10-step protocol to streamline analysis of data that will enhance understanding of the data, the statistical models and the results, and optimize communication with the reader with respect to both the procedure and the outcomes. The protocol takes the investigator from study design and organization of data (formulating relevant questions, visualizing data collection, data exploration, identifying dependency), through conducting analysis (presenting, fitting and validating the model) and presenting output (numerically and visually), to extending the model via simulation. Each step includes procedures to clarify aspects of the data that affect statistical analysis, as well as guidelines for written presentation. Steps are illustrated with examples using data from the literature.
* Following this protocol will reduce the organization, analysis and presentation of what may be an overwhelming information avalanche into sequential and, more to the point, manageable, steps. It provides guidelines for selecting optimal statistical tools to assess data relevance and significance, for choosing aspects of the analysis to include in a published report and for clearly communicating information.},
language = {en},
number = {6},
urldate = {2016-06-17},
journal = {Methods in Ecology and Evolution},
author = {Zuur, Alain F. and Ieno, Elena N.},
month = jun,
year = {2016},
keywords = {Visualization, effective communication, protocol, statistical analysis},
pages = {636--645}
}
@misc{annkemery_data_2014,
title = {Data {Visualization} {Checklist}},
url = {http://annkemery.com/portfolio/dataviz-checklist/},
abstract = {Stephanie Evergreen and I created the Data Visualization Checklist to provide guidance on how, exactly, to make effective graphs},
urldate = {2016-07-09},
journal = {Ann's Blog},
month = may,
year = {2014}
}
@article{rougier_ten_2014,
title = {Ten {Simple} {Rules} for {Better} {Figures}},
volume = {10},
issn = {1553-7358},
url = {http://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1003833},
doi = {10.1371/journal.pcbi.1003833},
number = {9},
urldate = {2016-12-21},
journal = {PLOS Computational Biology},
author = {Rougier, Nicolas P. and Droettboom, Michael and Bourne, Philip E.},
month = sep,
year = {2014},
keywords = {data visualization, Research Design, Software tools, Vision, Software design, Radii, Eye movements, Seismic signal processing},
pages = {e1003833}
}
@misc{rauser_how_2016,
title = {How {Humans} {See} {Data}},
url = {https://www.youtube.com/watch?v=fSgEeI2Xpdc},
abstract = {John Rauser explains a few of the most important results from research into the functioning of the human visual system and the question of how humans decode information presented in graphical form. By understanding and applying this research when designing statistical graphics, you can simplify difficult analytical tasks as much as possible.},
urldate = {2017-07-24},
author = {{John Rauser}},
month = dec,
year = {2016},
keywords = {data, PSYCHOLOGY, statistics, Visualization, graphs, monitoring, velocity}
}
@techreport{broman_data_2017,
title = {Data organization in spreadsheets},
url = {https://peerj.com/preprints/3183v1/},
abstract = {Spreadsheets are widely used software tools for data entry, storage, analysis, and visualization. Focusing on the data entry and storage aspects, this paper offers practical recommendations for organizing spreadsheet data to reduce errors and ease later analyses. The basic principles are: be consistent, write dates like YYYY-MM-DD, don't leave any cells empty, put just one thing in a cell, organize the data as a single rectangle (with subjects as rows and variables as columns, and with a single header row), create a data dictionary, don't include calculations in the raw data files, don't use font color or highlighting as data, choose good names for things, make backups, use data validation to avoid data entry errors, and save the data in plain text file.},
language = {eng},
urldate = {2017-08-31},
institution = {PeerJ Preprints},
author = {Broman, Karl W and Woo, Kara H.},
month = aug,
year = {2017},
note = {DOI: 10.7287/peerj.preprints.3183v1}
}
@book{noauthor_data_nodate-1,
title = {Data {Visualization} for {Social} {Science}},
url = {http://socviz.co/},
abstract = {A practical introduction with R and ggplot2.},
urldate = {2017-09-09},
file = {Snapshot:/home/bolker/.mozilla/firefox/f2nw6467.default/zotero/storage/MTXFEB3J/socviz.co.html:text/html}
}
@article{tufte_dataink_1990,
title = {Data-{Ink} {Maximization} and {Graphical} {Design}},
volume = {58},
copyright = {Copyright © 1990 Nordic Society Oikos},
issn = {0030-1299},
url = {http://www.jstor.org/stable/3545420},
doi = {10.2307/3545420},
number = {2},
urldate = {2013-01-03},
journal = {Oikos},
author = {Tufte, E. R.},
month = jun,
year = {1990},
note = {ArticleType: research-article / Full publication date: Jun., 1990 / Copyright © 1990 Nordic Society Oikos},
pages = {130--144}
}
@book{tufte_visual_2001,
edition = {2d},
title = {The {Visual} {Display} of {Quantitative} {Information}},
publisher = {Graphics Press},
author = {Tufte, Edward},
year = {2001}
}
@book{tufte_beautiful_2006,
address = {Cheshire, Conn.},
title = {Beautiful evidence},
isbn = {0-9613921-7-7 978-0-9613921-7-8},
language = {English},
publisher = {Graphics Press},
author = {Tufte, Edward R},
year = {2006}
}
@book{tufte_envisioning_1995,
address = {Cheshire, Conn.},
title = {Envisioning information},
isbn = {0-9613921-1-8 978-0-9613921-1-6},
language = {English},
publisher = {Graphics Press},
author = {Tufte, Edward R},
year = {1995}
}
@book{tufte_visual_1997,
address = {Cheshire, Conn.},
title = {Visual explanations: images and quantities, evidence and narrative},
isbn = {0-9613921-2-6 978-0-9613921-2-3},
shorttitle = {Visual explanations},
language = {English},
publisher = {Graphics Press},
author = {Tufte, Edward R},
year = {1997}
}
@article{gelman_infovis_2013,
title = {Infovis and {Statistical} {Graphics}: {Different} {Goals}, {Different} {Looks}},
volume = {22},
issn = {1061-8600},
shorttitle = {Infovis and {Statistical} {Graphics}},
url = {http://www.tandfonline.com/doi/abs/10.1080/10618600.2012.761137},
doi = {10.1080/10618600.2012.761137},
abstract = {The importance of graphical displays in statistical practice has been recognized sporadically in the statistical literature over the past century, with wider awareness following Tukey's Exploratory Data Analysis and Tufte's books in the succeeding decades. But statistical graphics still occupy an awkward in-between position: within statistics, exploratory and graphical methods represent a minor subfield and are not well integrated with larger themes of modeling and inference. Outside of statistics, infographics (also called information visualization or Infovis) are huge, but their purveyors and enthusiasts appear largely to be uninterested in statistical principles. We present here a set of goals for graphical displays discussed primarily from the statistical point of view and discuss some inherent contradictions in these goals that may be impeding communication between the fields of statistics and Infovis. One of our constructive suggestions, to Infovis practitioners and statisticians alike, is to try not to cram into a single graph what can be better displayed in two or more. We recognize that we offer only one perspective and intend this article to be a starting point for a wide-ranging discussion among graphic designers, statisticians, and users of statistical methods. The purpose of this article is not to criticize but to explore the different goals that lead researchers in different fields to value different aspects of data visualization.},
number = {1},
urldate = {2013-07-01},
journal = {Journal of Computational and Graphical Statistics},
author = {Gelman, Andrew and Unwin, Antony},
year = {2013},
pages = {2--28}
}
@misc{camoes_what-would-tufte-say_nodate,
title = {The "what-would-{Tufte}-say" syndrome},
url = {http://www.excelcharts.com/blog/the-what-would-tufte-say-syndrome/},
abstract = {An alarming level of the "what-would-Tufte-say" syndrome can be found in this post and some of its comments discussing a New York Times's infographic. This syndrome has some recognizable features like the extensive use of "chart junk", "lie factor" or other terms and expressions coined by Tufte that reveal a somewhat},
urldate = {2017-01-10},
journal = {The Excel Charts Blog},
author = {Camoes, Jorge}
}
@article{cleveland_graphical_1984,
title = {Graphical {Perception}: {Theory}, {Experimentation}, and {Application} to the {Development} of {Graphical} {Methods}},
volume = {79},
issn = {01621459},
shorttitle = {Graphical {Perception}},
url = {http://www.jstor.org/stable/2288400},
doi = {10.2307/2288400},
abstract = {The subject of graphical methods for data analysis and for data presentation needs a scientific foundation. In this article we take a few steps in the direction of establishing such a foundation. Our approach is based on graphical perception-the visual decoding of information encoded on graphs-and it includes both theory and experimentation to test the theory. The theory deals with a small but important piece of the whole process of graphical perception. The first part is an identification of a set of elementary perceptual tasks that are carried out when people extract quantitative information from graphs. The second part is an ordering of the tasks on the basis of how accurately people perform them. Elements of the theory are tested by experimentation in which subjects record their judgments of the quantitative information on graphs. The experiments validate these elements but also suggest that the set of elementary tasks should be expanded. The theory provides a guideline for graph construction: Graphs should employ elementary tasks as high in the ordering as possible. This principle is applied to a variety of graphs, including bar charts, divided bar charts, pie charts, and statistical maps with shading. The conclusion is that radical surgery on these popular graphs is needed, and as replacements we offer alternative graphical forms-dot charts, dot charts with grouping, and framed-rectangle charts.},
number = {387},
urldate = {2011-01-03},
journal = {Journal of the American Statistical Association},
author = {Cleveland, William S. and McGill, Robert},
year = {1984},
note = {ArticleType: research-article / Full publication date: Sep., 1984 / Copyright © 1984 American Statistical Association},
pages = {531--554}
}
@book{cleveland_visualizing_1993,
address = {Summit, NJ},
title = {Visualizing {Data}},
publisher = {Hobart Press},
author = {Cleveland, William},
year = {1993}
}
@article{cleveland_graphical_1987,
title = {Graphical {Perception}: {The} {Visual} {Decoding} of {Quantitative} {Information} on {Graphical} {Displays} of {Data}},
volume = {150},
issn = {00359238},
shorttitle = {Graphical {Perception}},
url = {http://www.jstor.org/stable/2981473},
doi = {10.2307/2981473},
abstract = {Studies in graphical perception, both theoretical and experimental, provide a scientific foundation for the construction area of statistical graphics. From these studies a paradigm that has important applications for practice has begun to emerge. The paradigm is based on elementary codes: Basic geometric and textural aspects of a graph that encode the quantitative information. The methodology that can be invoked to study graphical perception is illustrated by an investigation of the shape parameter of a two-variable graph, a topic that has had much discussion, but little scientific study, for at least 70 years.},
number = {3},
urldate = {2011-01-03},
journal = {Journal of the Royal Statistical Society. Series A (General)},
author = {Cleveland, William S. and McGill, Robert},
month = jan,
year = {1987},
note = {ArticleType: research-article / Full publication date: 1987 / Copyright © 1987 Royal Statistical Society},
pages = {192--229}
}
@misc{broman_creating_nodate,
title = {Creating effective figures and tables},
url = {https://www.biostat.wisc.edu/~kbroman/presentations/graphs2017.pdf},
urldate = {2017-10-26},
author = {Broman, Karl W}
}
@article{gelman_all_1999,
title = {All maps of parameter estimates are misleading},
volume = {18},
url = {http://www.stat.columbia.edu/~gelman/research/published/allmaps.pdf},
number = {23},
urldate = {2017-08-09},
journal = {Statistics in medicine},
author = {Gelman, Andrew and Price, Phillip N. and {others}},
year = {1999},
pages = {3221--3234}
}
@misc{lindberg_viz_2017,
title = {viz-pub: {A} place to publish data-vizes},
shorttitle = {viz-pub},
url = {https://github.com/halhen/viz-pub},
urldate = {2017-11-07},
author = {Lindberg, Henrik},
month = nov,
year = {2017},
note = {original-date: 2017-06-08T08:40:42Z},
file = {Snapshot:/home/bolker/.mozilla/firefox/f2nw6467.default/zotero/storage/T4J3DPJF/viz-pub.html:text/html}
}
@Book{meeks_d3_2017,
author = {Elijah Meeks},
title = {D3.js in Action: Data visualization with JavaScript},
publisher = {Manning},
year = {2017},
edition = {2},
isbn = {9781617294488},
url = {https://www.manning.com/books/d3js-in-action-second-edition}
}
@article{you_heres_2017,
title = {Here’s the visual proof of why vaccines do more good than harm},
url = {http://www.sciencemag.org/news/2017/04/here-s-visual-proof-why-vaccines-do-more-good-harm},
abstract = {Vaccines have beat back infectious diseases. Bubbles represent reported U.S. cases, but not all diseases were notifiable in all years. For example, mumps was not reported until 1968, the year after a vaccine was licensed. Click or hover on a bubble or a dot on the timeline to view more details.},
journal = {Science},
author = {Jia You},
month = apr,
year = {2017}
}
@article{peltonen_visualizations_2009,
title = {Visualizations for assessing convergence and mixing of {Markov} chain {Monte} {Carlo} simulations},
volume = {53},
issn = {01679473},
url = {http://linkinghub.elsevier.com/retrieve/pii/S0167947309002461},
doi = {10.1016/j.csda.2009.07.001},
number = {12},
journal = {Computational Statistics \& Data Analysis},
author = {Peltonen, Jaakko and Venna, Jarkko and Kaski, Samuel},
month = oct,
year = {2009},
pages = {4453--4470}
}
@article{su_its_2008,
title = {It’s easy to produce chartjunk using {Microsoft}®{Excel} 2007 but hard to make good graphs},
volume = {52},
url = {http://www.sciencedirect.com/science?_ob=ArticleURL&_udi=B6V8V-4S1S6FC-6&_user=10&_rdoc=1&_fmt=&_orig=search&_sort=d&view=c&_acct=C000050221&_version=1&_urlVersion=0&_userid=10&md5=d3e57dcf23c1adccee012110b71fefcf},
doi = {10.1016/j.csda.2008.03.007},
abstract = {The purpose of default settings in a graphic tool is to make it easy to produce good graphics that accord with the principles of statistical graphics, e.g., [Tufte, E.R., 1990. Envisioning Information. Graphics Press, Cheshire, Conn, Tufte, E.R., 1997. Visual Explanations: Images and Quantities, Evidence and Narrative, 2nd Edition. Graphics Press, Cheshire, Conn, Cleveland, W.S., 1993. Visualizing Data. Hobart Press, N.J Cleveland, W.S., 1994. The Elements of Graphing Data, rev. edition. AT\&T Bell Laboratories, Murray Hill, N.J, Wainer, H., 1997. Visual revelations: Graphical tales of fate and deception from Napoleon to Ross Perot. Copernicus, New York, Spence, R., 2001. Information Visualization. ACM Press \& AddisonWesley, New York, and Few, S., 2004. Show Me the Numbers. Analytic Press, Hillsdale, NJ]. If the defaults do not embody these principles, then the only way to produce good graphics is to be sufficiently familiar with the principles of statistical graphics. This paper shows that Excel graphics defaults do not embody the appropriate principles. Users who want to use Excel are advised to know the principles of good graphics well enough so that they can choose the appropriate options to override the defaults. Microsoft® should overhaul the Excel graphics engine so that its defaults embody the principles of statistical graphics and make it easy for non-experts to produce good graphs.},
number = {10},
urldate = {2008-07-04},
journal = {Computational Statistics \& Data Analysis},
author = {Su, Yu-Sung},
month = jun,
year = {2008},
pages = {4594--4601}
}
@article{gelman_why_2011,
title = {Why {Tables} {Are} {Really} {Much} {Better} {Than} {Graphs}},
volume = {20},
issn = {1061-8600},
url = {http://pubs.amstat.org/doi/abs/10.1198/jcgs.2011.09166},
doi = {10.1198/jcgs.2011.09166},
number = {1},
urldate = {2011-08-15},
journal = {Journal of Computational and Graphical Statistics},
author = {Gelman, Andrew},
month = mar,
year = {2011},
pages = {3--7}
}
@article{gelman_lets_2002,
title = {Let's practice what we preach: turning tables into graphs},
volume = {56},
shorttitle = {Let's practice what we preach},
url = {http://www.tandfonline.com/doi/abs/10.1198/000313002317572790},
number = {2},
urldate = {2016-02-01},
journal = {The American Statistician},
author = {Gelman, Andrew and Pasarica, Cristian and Dodhia, Rahul},
year = {2002},
pages = {121--130}
}
@article{gelman_all_1999,
title = {All maps of parameter estimates are misleading},
volume = {18},
url = {http://www.stat.columbia.edu/~gelman/research/published/allmaps.pdf},
number = {23},
urldate = {2017-08-09},
journal = {Statistics in medicine},
author = {Gelman, Andrew and Price, Phillip N. and {others}},
year = {1999},
pages = {3221--3234}
}
@article{gelman_tradeoffs_2013,
title = {Tradeoffs in {Information} {Graphics}},
volume = {22},
issn = {1061-8600},
url = {http://www.tandfonline.com/doi/abs/10.1080/10618600.2012.761141},
doi = {10.1080/10618600.2012.761141},
number = {1},
urldate = {2013-06-03},
journal = {Journal of Computational and Graphical Statistics},
author = {Gelman, Andrew and Unwin, Antony},
year = {2013},
pages = {45--49}
}
@misc{drum_yet_2017,
title = {Yet more chart geekery},
url = {http://www.motherjones.com/kevin-drum/2017/12/yet-more-chart-geekery/},
urldate = {2018-01-01},
journal = {Mother Jones},
author = {Drum, Kevin}
}
@misc{drang_drum_2017,
title = {Drum and {Tufte} and grids and axes - {All} this},
url = {http://leancrew.com/all-this/2017/12/drum-tufte-grids-axes/},
urldate = {2018-01-01},
author = {{Dr. Drang}}
}
@article{dawson_how_2011,
title = {How significant is a boxplot outlier},
volume = {19},
number = {2},
journal = {Journal of Statistics Education},
author = {Dawson, Robert},
year = {2011},
pages = {1--12}
}
@article{mcgill_variations_1978,
title = {Variations of {Box} {Plots}},
volume = {32},
issn = {0003-1305},
url = {http://www.jstor.org/stable/2683468},
doi = {10.2307/2683468},
abstract = {Box plots display batches of data. Five values from a set of data are conventionally used; the extremes, the upper and lower hinges (quartiles), and the median. Such plots are becoming a widely used tool in exploratory data analysis and in preparing visual summaries for statisticians and nonstatisticians alike. Three variants of the basic display, devised by the authors, are described. The first visually incorporates a measure of group size; the second incorporates an indication of rough significance of differences between medians; the third combines the features of the first two. These techniques are displayed by examples.},
number = {1},
urldate = {2018-01-10},
journal = {The American Statistician},
author = {McGill, Robert and Tukey, John W. and Larsen, Wayne A.},
year = {1978},
pages = {12--16}
}
@misc{beus_redesign_2018,
title = {Redesign of a truly bananas chart},
url = {https://medium.com/tdebeus/redesign-of-a-truly-bananas-chart-1617f930808d},
abstract = {On Twitter, I stumbled upon this horrendous 3D bar chart. When looking at the data, it might have been made in 2005. Data visualisation as…},
urldate = {2018-01-09},
journal = {Colourful Facts},
author = {Beus, Thomas de},
month = jan,
year = {2018}
}
@misc{debeus_contribute_2017,
title = {colourful-facts repository},
url = {https://github.com/thomasdebeus/colourful-facts},
urldate = {2018-01-09},
author = {de Beus, Thomas},
month = jul,
year = {2017},
note = {original-date: 2017-07-24T11:35:18Z}
}
@article{noauthor_chance_2008,
title = {{CHANCE} {Graphic} {Display} {Contest}: {Burtin}'s {Antibiotic} {Data}},
volume = {21},
issn = {0933-2480},
shorttitle = {{CHANCE} {Graphic} {Display} {Contest}},
url = {https://doi.org/10.1080/09332480.2008.10722935},
doi = {10.1080/09332480.2008.10722935},
number = {4},
urldate = {2018-01-15},
journal = {CHANCE},
month = sep,
year = {2008},
pages = {62--62}
}
@misc{sciani_cividis_2018,
title = {cividis: {Implementation} of the {Matplotlib} 'viridis' color map in {R} (lite version)},
shorttitle = {cividis},
url = {https://github.com/marcosci/cividis},
urldate = {2018-01-15},
author = {Sciani, Marco},
month = jan,
year = {2018},
note = {original-date: 2018-01-15T07:56:06Z}
}
@article{nunez_optimizing_2017,
title = {Optimizing colormaps with consideration for color vision deficiency to enable accurate interpretation of scientific data},
journal = {arXiv preprint arXiv:1712.01662},
author = {Nuñez, Jamie R. and Anderton, Chris R. and Renslow, Ryan S.},
year = {2017}
}
@misc{elliott_39_2016,
title = {39 studies about human perception in 30 minutes},
url = {https://medium.com/@kennelliott/39-studies-about-human-perception-in-30-minutes-4728f9e31a73},
abstract = {These are my speaker notes from a talk I gave at OpenVis in April 2016. Originally this talk was supposed to be called “Everything we know…},
urldate = {2018-01-16},
journal = {Medium},
author = {Elliott, Kennedy},
month = may,
year = {2016}
}
@inproceedings{heer_crowdsourcing_2010,
title = {Crowdsourcing graphical perception: using mechanical turk to assess visualization design},
shorttitle = {Crowdsourcing graphical perception},
booktitle = {Proceedings of the {SIGCHI} {Conference} on {Human} {Factors} in {Computing} {Systems}},
publisher = {ACM},
author = {Heer, Jeffrey and Bostock, Michael},
year = {2010},
pages = {203--212}
}
@TechReport{boxplots,
author = {Hadley Wickham and Lisa Stryjewski},
institution = {had.co.nz},
title = {40 years of boxplots},
year = {2012},
url = {http://vita.had.co.nz/papers/boxplots.pdf}
}
@article{nunez_optimizing_2017,
title = {Optimizing colormaps with consideration for color vision deficiency to enable accurate interpretation of scientific data},
journal = {arXiv preprint arXiv:1712.01662},
author = {Nuñez, Jamie R. and Anderton, Chris R. and Renslow, Ryan S.},
year = {2017}
}
@Article{tibshirani_estimating_1987,
author = {Rob Tibshirani},
title = {Estimating optimal transformations for regression},
journal = {Journal of the American Statistical Association},
year = {1987},
volume = {83},
pages = {394}
}
@BOOK{QuinnKeough2002,
title = {Experimental Design and Data Analysis for Biologists},
publisher = {Cambridge University Press},
year = {2002},
author = {Gerry P. Quinn and Michael J. Keough},
address = {Cambridge, England},
isbn = {0521009766}
}
@article{gelman_exploratory_2004,
title = {Exploratory {Data} {Analysis} for {Complex} {Models}},
volume = {13},
issn = {1061-8600, 1537-2715},
url = {http://www.tandfonline.com/doi/abs/10.1198/106186004X11435},
doi = {10.1198/106186004X11435},
language = {en},
number = {4},
urldate = {2018-01-24},
journal = {Journal of Computational and Graphical Statistics},
author = {Gelman, Andrew},
month = dec,
year = {2004},
pages = {755--779}
}
@Article{zeileis_object_2006,
author = {Achim Zeileis},
title = {Object-Oriented Computation of Sandwich Estimators},
journal = {Journal of Statistical Software},
year = {2006},
volume = {16},
number = {9},
pages = {1-16},
url = {http://www.jstatsoft.org/v16/i09/}
}
@article{hosmer_comparison_1997,
title = {A comparison of goodness-of-fit tests for the logistic regression model},
volume = {16},
number = {9},
journal = {Statistics in medicine},
author = {Hosmer, David W. and Hosmer, Trina and Le Cessie, Saskia and Lemeshow, Stanley},
year = {1997},
pages = {965--980}
}
@inproceedings{swayne_exploratory_2004,
title = {Exploratory visual analysis of graphs in {GGobi}},
booktitle = {Proceeds of the 3d International Workshop on Distributed Statistical Computing (DSC 2003)},
publisher = {Springer},
author = {Swayne, Deborah F. and Buja, Andreas and Lang, Duncan Temple},
year = {2004},
editor = {K. Hornik and F. Leisch},
pages = {477--488},
url = {https://link.springer.com/chapter/10.1007/978-3-7908-2656-2_39}
}
@article{buja_statistical_2009,
title = {Statistical inference for exploratory data analysis and model diagnostics},
volume = {367},
issn = {1364-503X},
url = {http://rsta.royalsocietypublishing.org/cgi/doi/10.1098/rsta.2009.0120},
doi = {10.1098/rsta.2009.0120},
number = {1906},
journal = {Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences},
author = {Buja, A. and Cook, D. and Hofmann, H. and Lawrence, M. and Lee, E.-K. and Swayne, D. F. and Wickham, H.},
month = oct,
year = {2009},
pages = {4361--4383}
}
@article{augustin_quantile_2012,
title = {On quantile quantile plots for generalized linear models},
volume = {56},
issn = {01679473},
url = {http://linkinghub.elsevier.com/retrieve/pii/S0167947312000692},
doi = {10.1016/j.csda.2012.01.026},
number = {8},
urldate = {2013-07-01},
journal = {Computational Statistics \& Data Analysis},
author = {Augustin, Nicole H. and Sauleau, Erik-André and Wood, Simon N.},
month = aug,
year = {2012},
pages = {2404--2409}
}
@misc{meeks_color_2018,
title = {Color {Advice} for {Data} {Visualization} with {D}3.js},
url = {https://medium.com/@Elijah_Meeks/color-advice-for-data-visualization-with-d3-js-33b5adc41c90},
abstract = {Using color in a post-category20 world},
urldate = {2018-02-02},
journal = {Elijah Meeks},
author = {Meeks, Elijah},
month = jan,
year = {2018}
}
@phdthesis{wei_extending_2017,
type = {Thesis},
title = {Extending {Growth} {Mixture} {Models} and {Handling} {Missing} {Values} via {Mixtures} of {Non}-{Elliptical} {Distributions}},
url = {https://macsphere.mcmaster.ca/handle/11375/21987},
abstract = {Growth mixture models (GMMs) are used to model intra-individual change and inter-individual differences in change and to detect underlying group structure in longitudinal studies. Regularly, these models are fitted under the assumption of normality, an assumption that is frequently invalid. To this end, this thesis focuses on the development of novel non-elliptical growth mixture models to better fit real data. Two non-elliptical growth mixture models, via the multivariate skew-t distribution and the generalized hyperbolic distribution, are developed and applied to simulated and real data. Furthermore, these two non-elliptical growth mixture models are extended to accommodate missing values, which are near-ubiquitous in real data.
Recently, finite mixtures of non-elliptical distributions have flourished and facilitated the flexible clustering of the data featuring longer tails and asymmetry. However, in practice, real data often have missing values, and so work in this direction is also pursued. A novel approach, via mixtures of the generalized hyperbolic distribution and mixtures of the multivariate skew-t distributions, is presented to handle missing values in mixture model-based clustering context. To increase parsimony, families of mixture models have been developed by imposing constraints on the component scale matrices whenever missing data occur. Next, a mixture of generalized hyperbolic factor analyzers model is also proposed to cluster high-dimensional data with different patterns of missing values. Two missingness indicator matrices are also introduced to ease the computational burden. The algorithms used for parameter estimation are presented, and the performance of the methods is illustrated on simulated and real data.},
language = {en},
urldate = {2018-02-04},
author = {Wei, Yuhong},
year = {2017}
}
@article{schielzeth_simple_2010,
title = {Simple means to improve the interpretability of regression coefficients},
url = {http://dx.doi.org/10.1111/j.2041-210X.2010.00012.x},
doi = {10.1111/j.2041-210X.2010.00012.x},
abstract = {1. Linear regression models are an important statistical tool in evolutionary and ecological studies. Unfortunately, these models often yield some uninterpretable estimates and hypothesis tests, especially when models contain interactions or polynomial terms. Furthermore, the standard errors for treatment groups, although often of interest for including in a publication, are not directly available in a standard linear model. 2. Centring and standardization of input variables are simple means to improve the interpretability of regression coefficients. Further, refitting the model with a slightly modified model structure allows extracting the appropriate standard errors for treatment groups directly from the model. 3. Centring will make main effects biologically interpretable even when involved in interactions and thus avoids the potential misinterpretation of main effects. This also applies to the estimation of linear effects in the presence of polynomials. Categorical input variables can also be centred and this sometimes assists interpretation. 4. Standardization (z-transformation) of input variables results in the estimation of standardized slopes or standardized partial regression coefficients. Standardized slopes are comparable in magnitude within models as well as between studies. They have some advantages over partial correlation coefficients and are often the more interesting standardized effect size. 5. The thoughtful removal of intercepts or main effects allows extracting treatment means or treatment slopes and their appropriate standard errors directly from a linear model. This provides a simple alternative to the more complicated calculation of standard errors from contrasts and main effects. 6. The simple methods presented here put the focus on parameter estimation (point estimates as well as confidence intervals) rather than on significance thresholds. They allow fitting complex, but meaningful models that can be concisely presented and interpreted. The presented methods can also be applied to generalised linear models {(GLM)} and linear mixed models.},
volume = {1},
pages = {103-113},
journal = {Methods in Ecology and Evolution},
author = {Schielzeth, Holger},
year = {2010}
}
@article{gelman_scaling_2008,
title = {Scaling regression inputs by dividing by two standard deviations},
volume = {27},
issn = {02776715, 10970258},
url = {http://doi.wiley.com/10.1002/sim.3107},
doi = {10.1002/sim.3107},
language = {en},
number = {15},
urldate = {2018-02-04},
journal = {Statistics in Medicine},
author = {Gelman, Andrew},
month = jul,
year = {2008},
pages = {2865--2873}
}
@article{schultz_evidence_2016,
title = {Evidence for a trophic cascade on rocky reefs following sea star mass mortality in {British} {Columbia}},
volume = {4},
issn = {2167-8359},
url = {https://peerj.com/articles/1980},
doi = {10.7717/peerj.1980},
abstract = {Echinoderm population collapses, driven by disease outbreaks and climatic events, may be important drivers of population dynamics, ecological shifts and biodiversity. The northeast Pacific recently experienced a mass mortality of sea stars. In Howe Sound, British Columbia, the sunflower star Pycnopodia helianthoides—a previously abundant predator of bottom-dwelling invertebrates—began to show signs of a wasting syndrome in early September 2013, and dense aggregations disappeared from many sites in a matter of weeks. Here, we assess changes in subtidal community composition by comparing the abundance of fish, invertebrates and macroalgae at 20 sites in Howe Sound before and after the 2013 sea star mortality to evaluate evidence for a trophic cascade. We observed changes in the abundance of several species after the sea star mortality, most notably a four-fold increase in the number of green sea urchins, Strongylocentrotus droebachiensis, and a significant decline in kelp cover, which are together consistent with a trophic cascade. Qualitative data on the abundance of sunflower stars and green urchins from a citizen science database show that the patterns of echinoderm abundance detected at our study sites reflected wider local trends. The trophic cascade evident at the scale of Howe Sound was observed at half of the study sites. It remains unclear whether the urchin response was triggered directly, via a reduction in urchin mortality, or indirectly, via a shift in urchin distribution into areas previously occupied by the predatory sea stars. Understanding the ecological implications of sudden and extreme population declines may further elucidate the role of echinoderms in temperate seas, and provide insight into the resilience of marine ecosystems to biological disturbances.},
language = {en},
urldate = {2018-02-06},
journal = {PeerJ},
author = {Schultz, Jessica A. and Cloutier, Ryan N. and Côté, Isabelle M.},
month = apr,
year = {2016},
pages = {e1980}
}
@article{mccallum_situ_2017,
title = {In situ exposure to wastewater effluent reduces survival but has little effect on the behaviour or physiology of an invasive {Great} {Lakes} fish},
volume = {184},
issn = {0166-445X},
url = {http://www.sciencedirect.com/science/article/pii/S0166445X16303757},
doi = {10.1016/j.aquatox.2016.12.017},
abstract = {Treated effluents from wastewater treatment plants (WWTP) are a significant source of anthropogenic contaminants, such as pharmaceuticals, in the aquatic environment. Although our understanding of how wastewater effluent impacts fish reproduction is growing, we know very little about how effluent affects non-reproductive physiology and behaviours associated with fitness (such as aggression and activity). To better understand how fish cope with chronic exposure to wastewater effluent in the wild, we caged round goby (Neogobius melanostomus) for three weeks at different distances from a wastewater outflow. We evaluated the effects of this exposure on fish survival, behaviour, metabolism, and respiratory traits. Fish caged inside the WWTP and close to the outfall experienced higher mortality than fish from the reference site. Interestingly, those fish that survived the exposure performed similarly to fish caged at the reference site in tests of aggressive behaviour, startle-responses, and dispersal. Moreover, the fish near WWTP outflow displayed similar resting metabolism (O2 consumption rates), hypoxia tolerance, haemoglobin concentration, haematocrit, and blood-oxygen binding affinities as the fish from the more distant reference site. We discuss our findings in relation to exposure site water quality, concentrations of pharmaceutical and personal care product pollutants, and our test species tolerance.},
urldate = {2018-02-06},
journal = {Aquatic Toxicology},
author = {McCallum, Erin S. and Du, Sherry N. N. and Vaseghi-Shanjani, Maryam and Choi, Jasmine A. and Warriner, Theresa R. and Sultana, Tamanna and Scott, Graham R. and Balshine, Sigal},
month = mar,
year = {2017},
keywords = {Round goby, Activity, Caging, Cootes Paradise Marsh, PPCPs, Respirometry},
pages = {37--48}
}
@inproceedings{bateman_useful_2010,
title = {Useful junk?: the effects of visual embellishment on comprehension and memorability of charts},
shorttitle = {Useful junk?},
booktitle = {Proceedings of the {SIGCHI} {Conference} on {Human} {Factors} in {Computing} {Systems}},
publisher = {ACM},
author = {Bateman, Scott and Mandryk, Regan L. and Gutwin, Carl and Genest, Aaron and McDine, David and Brooks, Christopher},
year = {2010},
pages = {2573--2582}
}
@article{borkin_beyond_2016,
title = {Beyond {Memorability}: {Visualization} {Recognition} and {Recall}},
volume = {22},
issn = {1077-2626},
shorttitle = {Beyond {Memorability}},
url = {http://ieeexplore.ieee.org/document/7192646/},
doi = {10.1109/TVCG.2015.2467732},
number = {1},
urldate = {2018-02-09},
journal = {IEEE Transactions on Visualization and Computer Graphics},
author = {Borkin, Michelle A. and Bylinskii, Zoya and Kim, Nam Wook and Bainbridge, Constance May and Yeh, Chelsea S. and Borkin, Daniel and Pfister, Hanspeter and Oliva, Aude},
month = jan,
year = {2016},
pages = {519--528}
}
@book{doumont_trees_2009,
address = {Kraainem},
title = {Trees, {Maps}, and {Theorems} {Effective} {Communication} for {Rational} {Minds}},
isbn = {978-90-813677-0-7},
abstract = {The book comprises five parts: first, fundamentals, then the written documents, oral presentations, and graphical displays, and finally the application of these ideas to more specific types of document.},
language = {English},
publisher = {Principiae},
author = {Doumont, Jean-Luc},
year = {2009}
}
@article{murrell_infovis_2013,
title = {{InfoVis} and {Statistical} {Graphics}: {Comment}},
volume = {22},
issn = {1061-8600},
shorttitle = {{InfoVis} and {Statistical} {Graphics}},
url = {https://doi.org/10.1080/10618600.2012.751875},
doi = {10.1080/10618600.2012.751875},
number = {1},
urldate = {2018-02-12},
journal = {Journal of Computational and Graphical Statistics},
author = {Murrell, Paul},
month = jan,
year = {2013},
pages = {33--37},
file = {Snapshot:/home/bolker/.mozilla/firefox/f2nw6467.default/zotero/storage/RPZE7DQ8/10618600.2012.html:text/html}
}
@article{kosara_infovis_2013,
title = {{InfoVis} {Is} {So} {Much} {More}: {A} {Comment} on {Gelman} and {Unwin} and an {Invitation} to {Consider} the {Opportunities}},
volume = {22},
issn = {1061-8600},
shorttitle = {{InfoVis} {Is} {So} {Much} {More}},
url = {https://doi.org/10.1080/10618600.2012.755465},
doi = {10.1080/10618600.2012.755465},
number = {1},
urldate = {2018-02-12},
journal = {Journal of Computational and Graphical Statistics},
author = {Kosara, Robert},
month = jan,
year = {2013},
pages = {29--32},
file = {Snapshot:/home/bolker/.mozilla/firefox/f2nw6467.default/zotero/storage/UTYES3JA/10618600.2012.html:text/html}
}
@book{pugin_true_1853,
title = {The true principles of pointed or {Christian} architecture: set forth in two lectures delivered at {St}. {Marie}'s, {Oscott}},
shorttitle = {The true principles of pointed or {Christian} architecture},
url = {https://books.google.ca/books?id=QphZAAAAYAAJ},
language = {en},
publisher = {H. G. Bohn},
author = {Pugin, Augustus Welby Northmore},
year = {1853},
note = {Google-Books-ID: QphZAAAAYAAJ},
keywords = {Architecture / General, Architecture / History / General, Architecture / Religious Buildings, Architecture, Gothic}
}
@misc{noren_cost_2011,
title = {Cost of {Health} {Care} by {Country}},
url = {https://thesocietypages.org/graphicsociology/2011/04/26/cost-of-health-care-by-country-national-geographic/},
abstract = {The Society Pages (TSP) is an open-access social science project headquartered in the Department of Sociology at the University of Minnesota},
language = {en},
urldate = {2018-02-12},
journal = {Graphic Sociology},
author = {Noren, Laura},
month = apr,