
@inproceedings{Pruim:MinimalR:2011,
  title = {Teaching Statistics with {R}},
  author = {Randall Pruim},
  year = 2011,
  booktitle = {Joint Statistics Meetings Roundtable}
  }
  
@inproceedings{Wang:USCOTS:2015,
  title = {Visualization as the Gateway Drug to Statistics in Week One},
  author = {Xiaofei (Susan) Wang and Cynthia Rush},
  year = 2015,
  booktitle = {United States Conference on Teaching Statistics}
  }

@Manual{R,
  title = {R: A Language and Environment for Statistical Computing},
  author = {{R Core Team}},
  organization = {R Foundation for Statistical Computing},
  address = {Vienna, Austria},
  year = {2012},
  note = {{ISBN} 3-900051-07-0},
  url = {http://www.R-project.org/},
}

@article{ihaka:1996,
  Author = {Ihaka, Ross and Gentleman, Robert},
	Journal = {Journal of Computational and Graphical Statistics},
	Number = 3,
	Pages = {299--314},
	Title = {R: A Language for Data Analysis and Graphics},
	Volume = 5,
	Year = 1996}

@article{Baumer:RMarkdown:2014,
  author = {Baumer, Ben and {Cetinkaya-Rundel}, Mine and 
    Bray, Andrew and Loi, Linda and Horton, Nicholas J},
  year = {2014},
  title = {R Markdown: Integrating A Reproducible Analysis Tool into Introductory Statistics}, 
  journal = {Technology Innovations in Statistics Education},
  volume = 8,
  number = 1,
  url = {http://escholarship.org/uc/item/90b2f5xh}
  }
  
@article{Wild:RSS:2011,
  Author = {Wild, C J and Pfannkuch M and Regan M and Horton N J},
  Title = {Towards more accessible conceptions of statistical inference}, 
  Journal = {Journal of the Royal Statistical Society: Series A (Statistics in Society)},
  Year = 2011,
  volume = {174 (part 2)},
  pages = {247--295}
  } 

@article{Hesterberg:2015,
  Author = {Tim C. Hesterberg},
  Title = {What Teachers Should Know about the Bootstrap: Resampling in the Undergraduate Statistics Curriculum},
  Year = 2015, 
  Journal = {The American Statistician}
}

@article{NolanTempleLang:2010,
  Author = {Deborah Nolan and Duncan Temple Lang},
  Year = 2010,
  Title = {Computing in the Statistics Curricula}, 
  Journal = {The American Statistician}, 
  Volume = 64,
  Number = 2, 
  pages = {97--107}, 
  url = {http://dx.doi.org/10.1198/tast.2010.09132}
}

@article{Ridgway:2015,
  Title = {Implications of the Data Revolution for Statistics Education},
  Author = {Ridgway, J},
  Journal = {International Statistical Review},
  Year = 2015
}

@article{HortonBaumerWickham:2015,
  Author = {Nicholas J. Horton and Benjamin S. Baumer and Hadley Wickham},
  Year = 2015,
  Title = {Setting the stage for data science: integration of data management skills in introductory and second courses in statistics},
  journal = {CHANCE},
  Volume = 28,
  Number = 2,
  Pages = {40--50}
}

@ARTICLE{2015arXiv150200318H,
   author = {{Horton}, N.~J. and {Baumer}, B.~S. and {Wickham}, H.},
    title = "{Setting the stage for data science: integration of data management skills in introductory and second courses in statistics}",
  journal = {ArXiv e-prints},
archivePrefix = "arXiv",
   eprint = {1502.00318},
 primaryClass = "stat.CO",
 keywords = {Statistics - Computation, Computer Science - Computers and Society, Statistics - Other Statistics, 62-01},
     year = 2015,
    month = feb,
   adsurl = {http://adsabs.harvard.edu/abs/2015arXiv150200318H},
  adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}


@ARTICLE{Tintle:TAS:2015,
   author = {{Tintle}, N. and {Chance}, B. and {Cobb}, G. and {Roy}, S. and 
	{Swanson}, T. and {VanderStoep}, J.},
    title = "{Combating anti-statistical thinking using simulation-based methods throughout the undergraduate curriculum}",
  journal = {The American Statistician},
   volume = 69,
   number = 4,
     year = 2015,
   adsurl = {http://adsabs.harvard.edu/abs/2015arXiv150800543T},
  adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}

@ARTICLE{Grolemund:ISR:2014,
title = {A Cognitive Interpretation of Data Analysis},
author = {Grolemund, Garrett and Wickham, Hadley},
year = {2014},
journal = {International Statistical Review},
volume = {82},
number = {2},
pages = {184--204},
abstract = {This paper proposes a scientific model to explain the analysis
process. We argue that data analysis is primarily a procedure to build
understanding, and as such, it dovetails with the cognitive processes of the
human mind. Data analysis tasks closely resemble the cognitive process known as
sensemaking. We demonstrate how data analysis is a sensemaking task adapted to
use quantitative data. This identification highlights a universal structure
within data analysis activities and provides a foundation for a theory of data
analysis. The competing tensions of cognitive compatibility and scientific
rigour create a series of problems that characterise the data analysis process.
These problems form a useful organising model for the data analysis task while
allowing methods to remain flexible and situation dependent. The insights of
this model are especially helpful for consultants, applied statisticians and
teachers of data analysis.},
url = {http://EconPapers.repec.org/RePEc:bla:istatr:v:82:y:2014:i:2:p:184-204}
}

@book{Salsburg:2002,
    abstract = {{Science is inextricably linked with mathematics. Statistician David Salsburg examines the development of ever-more-powerful statistical methods for determining scientific truth in <I>The Lady Tasting Tea</I>, a series of historical and biographical sketches that illuminate without alienating the mathematically timid. Salsburg, who has worked in academia and industry and has met many of the major players he writes about, shares his subjects' enthusiasm for problem solving and deep thinking. His sense of excitement drives the prose, but never at the expense of the reader; if anything, the author has taken pains to eliminate esoterica and ephemera from his stories. This might frustrate a few number-head readers, but the abundant notes and references should keep them happy in the library for weeks after reading the book.<p>  Ultimately, the various tales herein are unified in a single theme: the conversion of science from observational natural history into rigorously defined statistical models of data collection and analysis. This process, usually only implicit in studies of scientific methods and history, is especially important now that we seem to be reaching the point of diminishing returns and are looking for new paradigms of scientific investigation. <I>The Lady Tasting Tea</I> will appeal to a broad audience of scientifically literate readers, reminding them of the humanity underlying the work.  <I>--Rob Lightner</I>} {At a summer tea party in Cambridge, England, a guest states that tea poured into milk tastes different from milk poured into tea. Her notion is shouted down by the scientific minds of the group. But one man, Ronald Fisher, proposes to scientifically test the hypothesis. There is no better person to conduct such an experiment, for Fisher is a pioneer in the field of statistics. The Lady Tasting Tea spotlights not only Fishers theories but also the revolutionary ideas of dozens of men and women which affect our modern everyday lives. Writing with verve and wit, David Salsburg traces breakthroughs ranging from the rise and fall of Karl Pearsons theories to the methods of quality control that rebuilt postwar Japans economy, including a pivotal early study on the capacity of a small beer cask at the Guinness brewing factory. Brimming with intriguing tidbits and colorful characters, The Lady Tasting Tea salutes the spirit of those who dared to look at the world in a new way.}},
    author = {Salsburg, David},
    citeulike-article-id = {1660512},
    citeulike-linkout-0 = {http://www.amazon.ca/exec/obidos/redirect?tag=citeulike09-20\&amp;path=ASIN/0805071342},
    citeulike-linkout-1 = {http://www.amazon.de/exec/obidos/redirect?tag=citeulike01-21\&amp;path=ASIN/0805071342},
    citeulike-linkout-2 = {http://www.amazon.fr/exec/obidos/redirect?tag=citeulike06-21\&amp;path=ASIN/0805071342},
    citeulike-linkout-3 = {http://www.amazon.jp/exec/obidos/ASIN/0805071342},
    citeulike-linkout-4 = {http://www.amazon.co.uk/exec/obidos/ASIN/0805071342/citeulike00-21},
    citeulike-linkout-5 = {http://www.amazon.com/exec/obidos/redirect?tag=citeulike07-20\&path=ASIN/0805071342},
    citeulike-linkout-6 = {http://www.worldcat.org/isbn/0805071342},
    citeulike-linkout-7 = {http://books.google.com/books?vid=ISBN0805071342},
    citeulike-linkout-8 = {http://www.amazon.com/gp/search?keywords=0805071342\&index=books\&linkCode=qs},
    citeulike-linkout-9 = {http://www.librarything.com/isbn/0805071342},
    day = {01},
    howpublished = {Paperback},
    isbn = {0805071342},
    keywords = {book, reference, stat},
    month = may,
    posted-at = {2008-03-01 08:30:11},
    priority = {2},
    publisher = {Holt Paperbacks},
    title = {{The Lady Tasting Tea: How Statistics Revolutionized Science in the Twentieth Century}},
    year = {2002}
}


  @Manual{mosaic,
    title = {mosaic: Project MOSAIC Statistics and Mathematics Teaching Utilities},
    author = {Randall Pruim and Daniel Kaplan and Nicholas Horton},
    year = {2015},
    note = {R package version 0.12.9003},
  }


  @Book{lattice,
    title = {Lattice: Multivariate Data Visualization with R},
    author = {Deepayan Sarkar},
    publisher = {Springer},
    address = {New York},
    year = {2008},
    note = {ISBN 978-0-387-75968-5},
    url = {http://lmdvr.r-forge.r-project.org},
  }



  @Book{ggplot2,
    author = {Hadley Wickham},
    title = {ggplot2: Elegant Graphics for Data Analysis},
    publisher = {Springer-Verlag New York},
    year = {2009},
    isbn = {978-0-387-98140-6},
    url = {http://had.co.nz/ggplot2/book},
  }


  @Manual{resample,
    title = {resample: Resampling Functions},
    author = {Tim Hesterberg},
    year = {2015},
    note = {R package version 0.4},
    url = {https://CRAN.R-project.org/package=resample},
  }

  @Manual{dplyr,
    title = {dplyr: A Grammar of Data Manipulation},
    author = {Hadley Wickham and Romain Francois},
    note = {R package version 0.4.3.9000},
    url = {https://github.com/hadley/dplyr},
    year = 2015
  }

  @Manual{mosaicData,
    title = {mosaicData: Project MOSAIC (mosaic-web.org) data sets},
    author = {Randall Pruim and Daniel Kaplan and Nicholas Horton},
    year = {2015},
    note = {R package version 0.9.9001},
  }

