DataViz.bib

% Generated by Paperpile. Check out https://paperpile.com for more information.
% BibTeX export options can be customized via Settings -> BibTeX.

@BOOK{Wilke2019-il,
  title     = "Fundamentals of Data Visualization: A Primer on Making
               Informative and Compelling Figures",
  author    = "Wilke, Claus O",
  publisher = "O'Reilly Media",
  edition   =  1,
  year      =  2019,
  keywords  = "Module - DataViz",
  language  = "en",
  isbn      = "9781492031086"
}

@ARTICLE{Morey2016-yh,
  title       = "The fallacy of placing confidence in confidence intervals",
  author      = "Morey, Richard D and Hoekstra, Rink and Rouder, Jeffrey N and
                 Lee, Michael D and Wagenmakers, Eric-Jan",
  abstract    = "Interval estimates - estimates of parameters that include an
                 allowance for sampling uncertainty - have long been touted as
                 a key component of statistical analyses. There are several
                 kinds of interval estimates, but the most popular are
                 confidence intervals (CIs): intervals that contain the true
                 parameter value in some known proportion of repeated samples,
                 on average. The width of confidence intervals is thought to
                 index the precision of an estimate; CIs are thought to be a
                 guide to which parameter values are plausible or reasonable;
                 and the confidence coefficient of the interval (e.g., 95 \%)
                 is thought to index the plausibility that the true parameter
                 is included in the interval. We show in a number of examples
                 that CIs do not necessarily have any of these properties, and
                 can lead to unjustified or arbitrary inferences. For this
                 reason, we caution against relying upon confidence interval
                 theory to justify interval estimates, and suggest that other
                 theories of interval estimation should be used instead.",
  journal     = "Psychon. Bull. Rev.",
  volume      =  23,
  number      =  1,
  pages       = "103--123",
  month       =  feb,
  year        =  2016,
  url         = "http://dx.doi.org/10.3758/s13423-015-0947-8",
  keywords    = "Bayesian inference and parameter estimation; Bayesian
                 statistics; Statistical inference; Statistics;Bayes
                 Readings;Quantitative Methods;Module - Bayes;Module - DataViz",
  language    = "en",
  issn        = "1069-9384, 1531-5320",
  pmid        = "26450628",
  doi         = "10.3758/s13423-015-0947-8",
  pmc         = "PMC4742505",
  original_id = "51164b0f-7ced-081b-b3fd-bce8e49b8436"
}

@BOOK{Grolemund2017-jh,
  title     = "{R} for Data Science: Import, Tidy, Transform, Visualize, and
               Model Data",
  author    = "Grolemund, Garrett and Wickham, Hadley",
  publisher = "O'Reilly Media",
  edition   =  1,
  year      =  2017,
  keywords  = "Module - DataViz",
  language  = "en",
  isbn      = "9781491910399"
}

@BOOK{Healy2018-cx,
  title     = "Data Visualization: A Practical Introduction",
  author    = "Healy, Kieran",
  publisher = "Princeton University Press",
  edition   =  1,
  month     =  dec,
  year      =  2018,
  keywords  = "Module - DataViz",
  language  = "en",
  isbn      = "9780691181622"
}

@BOOK{Baumer2021-nm,
  title     = "Modern Data Science with {R}",
  author    = "Baumer, Benjamin S and Kaplan, Daniel T and Horton, Nicholas J",
  publisher = "Chapman and Hall/CRC",
  edition   =  2,
  month     =  apr,
  year      =  2021,
  keywords  = "Module - DataViz",
  language  = "en"
}

@BOOK{Wickham2016-tm,
  title     = "{ggplot2}: Elegant Graphics for Data Analysis",
  author    = "Wickham, Hadley",
  publisher = "Springer",
  edition   =  2,
  year      =  2016,
  keywords  = "Module - DataViz",
  language  = "en",
  isbn      = "9783319242750"
}