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@online{AdenBuie_tidyanimated,
author = {Garrick Aden‑Buie},
title = {Tidy Animated Verbs},
year = {2021},
url = {https://www.garrickadenbuie.com/project/tidyexplain/},
note = {Accessed: 2021-03-06}
}
@Book{Albert_2009,
title = {Bayesian Computation with R (Second Edition)},
author = {Jim Albert},
publisher = {Springer},
year = {2009},
isbn = {ISBN 978-0-387-92297-3},
}
@article{Anscombe_1973,
title = {Graphs in Statistical Analysis},
author = {F. J. Anscombe},
year = {1973},
journal = {The American Statistician},
volume = {27},
number = {1},
pages = {17-21},
DOI = {10.1080/00031305.1973.10478966},
url = {https://www.tandfonline.com/doi/abs/10.1080/00031305.1973.10478966}
}
@online{Ashton_2018,
title = {Where's my T-Shirt? Supply chain forecasting in fashion},
author = {Doug Ashton},
publisher = {Mango Solutions},
date = {2018},
urldate = {2018-09-13},
url = {https://www.slideshare.net/DouglasAshton1/wheres-my-tshirt-supply-chain-forecasting-in-fashion},
note = {Accessed: 2020-07-09}
}
@article{Baumer_2019,
author = {Benjamin S. Baumer},
title = {A Grammar for Reproducible and Painless Extract-Transform-Load Operations on Medium Data},
journal = {Journal of Computational and Graphical Statistics},
volume = {28},
number = {2},
pages = {256-264},
year = {2019},
publisher = {Taylor & Francis},
doi = {10.1080/10618600.2018.1512867},
URL = {
https://doi.org/10.1080/10618600.2018.1512867
},
eprint = {
https://doi.org/10.1080/10618600.2018.1512867
}
}
@Book{Bethlehem_2009,
title = {Applied Survey Methods: A Statistical Perspective},
author = {Jelke Bethlehem},
publisher = {Wiley},
series = {Wiley Series in Survey Methodology},
year = {2009},
isbn = {ISBN: 978-0-470-37308-8},
url = {https://www.wiley.com/en-ca/Applied+Survey+Methods:+A+Statistical+Perspective-p-9780470373088},
}
@article{Brewer_2003,
title = {A Transition in Improving Maps: The ColorBrewer Example},
author = {Cynthia A. Brewer},
year = {2003},
journal = {Cartography and Geographic Information Science},
volume = {30},
number = {2},
pages = {159-162},
DOI = {10.1559/152304003100011126},
url = {https://www.tandfonline.com/doi/abs/10.1559/152304003100011126}
}
@article{Brewer_etal_2003,
title = {ColorBrewer in Print: A Catalog of Color Schemes for Maps, Cartography and Geographic Information Science},
author = {Cynthia A. Brewer, Geoffrey W. Hatchard, Mark A. Harrower},
year = {2003},
journal = {Cartography and Geographic Information Science},
volume = {30},
number = {1},
pages = {5-32},
DOI = {10.1559/152304003100010929},
url = {https://www.tandfonline.com/doi/abs/10.1559/152304003100010929}
}
@inproceedings{Brickell_Shmatikov_2008,
author = {Brickell, Justin and Shmatikov, Vitaly},
year = {2008},
month = {08},
pages = {70-78},
title = {The cost of privacy: Destruction of data-mining utility in anonymized data publishing},
journal = {Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining},
doi = {10.1145/1401890.1401904},
url = {http://www.cs.cornell.edu/~shmat/shmat_kdd08.pdf}
}
@misc{Broman_tools4rr_2016,
title = {Tools for Reproducible Research: Organizing projects; exploratory data analysis},
author = {Karl Broman},
publisher = {Biostatistics & Medical Informatics, UW–Madison},
year = {2016},
urldate = {2015-05-14},
url = {https://kbroman.org/Tools4RR/assets/lectures/06_org_eda_withnotes.pdf}
}
@article{Broman_Woo_2017,
title = {Data organization in spreadsheets},
author = {Karl Broman and Kara Woo},
year = {2017},
journal = {The American Statistician},
volume = {72},
number = {1},
pages = {2-10},
DOI = {10.1080/00031305.2017.1375989},
url = {http://www.tandfonline.com/doi/full/10.1080/00031305.2017.1375989}
}
@online{Bryan_namingthings_2015,
title = {naming things},
author = {Jenny Bryan},
year = {2015},
urldate = {2015-05-14},
url = {http://www2.stat.duke.edu/~rcs46/lectures_2015/01-markdown-git/slides/naming-slides/naming-slides.pdf}
}
@online{Bryan_sanesheets_2016,
title = {sanesheets},
author = {Jenny Bryan},
year = {2016},
urldate = {2016-09-14},
url = {https://github.com/jennybc/sanesheets}
}
@online{Bryan_spreadsheets_2016,
title = {spreadsheets},
author = {Jenny Bryan},
year = {2016},
urldate = {2016-06-25},
url = {https://github.com/jennybc/2016-06_spreadsheets}
}
@online{Bryan_STAT545,
title = {STAT 545},
author = {Jenny Bryan and {The STAT 545 TAs}},
year = {2019},
urldate = {2019-10-14},
url = {https://stat545.com/}
}
@Book{Bryan_Hester_WTF,
title = {What They Forgot to Teach You About R},
author = {Jennifer Bryan,
Jim Hester,
Shannon Pileggi,
E. David Aja},
year = {2023},
url = {https://rstats.wtf/},
}
@Book{Bryan_etal_Happy_Git,
title = {Happy Git and GitHub for the useR},
author = {Jennifer Bryan,
the STAT 545 TAs,
Jim Hester},
year = {2020},
url = {https://happygitwithr.com/},
}
@Book{Buttrey_Whitaker_2017,
title = {A Data Scientist's Guide to Acquiring, Cleaning, and Managing Data in R},
author = {Samuel E. Buttrey and Lyn R. Whitaker},
publisher = {Wiley},
year = {2017},
isbn = {ISBN: 9781119080022},
url = {https://onlinelibrary.wiley.com/doi/book/10.1002/9781119080053},
}
@Book{Cairo_2013,
title = {The Functional Art: An Introduction to Information Graphics and Visualization},
author = {Alberto Cairo},
publisher = {New Riders},
year = {2013},
isbn = {ISBN 978-0-321-83473-7},
}
@Book{Cairo_2016,
title = {The Truthful Art: Data, Charts, and Maps for Communication},
author = {Alberto Cairo},
publisher = {New Riders},
year = {2016},
isbn = {ISBN 9780321934079},
}
@online{CampbellDollaghan_2018,
title = {Sorry, your data can still be identified even if it’s anonymized},
author = {Kelsey Campbell-Dollaghan},
publisher = {fastcompany.com},
date = {2018},
url = {https://www.fastcompany.com/90278465/sorry-your-data-can-still-be-identified-even-its-anonymized},
urldate = {2018-12-10},
note = {Accessed: 2020-06-24}
}
@article{Carmichael_Marron_2018,
doi = {},
url = {https://doi.org/10.1007/s42081-018-0009-3},
year = {2018},
month = {},
publisher = {},
volume = {1},
number = {1},
author = {Iain Carmichael and J.S. Marron},
title = {Data science vs. statistics: two cultures?},
journal = {Japanese Journal of Statistics and Data Science}
}
@article{Chan_2011,
title = {Principles and Practices of Analytical Method Validation: Validation of Analytical Methods is Time-consuming but essential},
author = {Chung Chow Chan},
year = {2011},
journal = {Quality Assurance Journal},
volume = {14},
pages = {61-64},
DOI = {10.1002/qaj.477},
url = {https://doi.org/10.1002/qaj.477}
}
@Book{Chang_2013,
title = {R Graphics Cookbook},
author = {Winston Chang},
publisher = {O'Reilly},
year = {2013},
isbn = {ISBN 978-1-449-31695-2},
url = {http://www.cookbook-r.com/Graphs/},
}
@Book{Chang_2018,
title = {R Graphics Cookbook},
edition = {second},
author = {Winston Chang},
publisher = {O'Reilly},
year = {2018},
isbn = {ISBN 9781491978603},
url = {https://r-graphics.org/},
}
@Book{Cleveland_1993,
title = {Visualizing Data},
author = {William S. Cleveland},
publisher = {Hobart Press},
year = {1993},
isbn = {ISBN 0-9634884-0-6},
}
@Book{Cleveland_1994,
title = {The Elements of Graphing Data},
author = {William S. Cleveland},
publisher = {Hobart Press},
year = {1994},
isbn = {ISBN 0-9634884-1-4},
}
@article{Cleveland_and_McGill_1984,
author = { William S. Cleveland and Robert McGill },
title = {Graphical Perception: Theory, Experimentation, and Application to the Development of Graphical Methods},
journal = {Journal of the American Statistical Association},
volume = {79},
number = {387},
pages = {531-554},
year = {1984},
publisher = {Taylor & Francis},
doi = {10.1080/01621459.1984.10478080},
URL = {
https://www.tandfonline.com/doi/abs/10.1080/01621459.1984.10478080
},
eprint = {
https://www.tandfonline.com/doi/pdf/10.1080/01621459.1984.10478080
}
}
@online{Conway_Venn_2010,
title = {The Data Science Venn Diagram},
author = {Drew Conway},
publisher = {drewconway.com},
date = {2010},
url = {http://drewconway.com/zia/2013/3/26/the-data-science-venn-diagram},
urldate = {2018-09-30},
note = {Accessed: 2020-07-04}
}
@Book{Criado_Perez_2019,
title = {Invisible Women: Data Bias in a World Designed for Men},
author = {Caroline Criado Perez},
publisher = {Abrams Press},
year = {2019},
isbn = {ISBN 978-1-4197-2907-2},
}
@Book{Cunningham_mixtape,
title = {Causal Inference: The Mixtape},
author = {Scott Cunningham},
publisher = {Yale University Press},
year = {2021},
isbn = {ISBN 9780300251685},
url = {https://mixtape.scunning.com/}
}
@Book{Davenport_Harris_2007,
title = {Competing on Analytics: The New Science of Winning},
author = {Thomas H. Davenport and
Jeanne G. Harris},
publisher = {Harvard Business School Press},
year = {2007},
isbn = {ISBN 978-1-4221-0332-6}
}
@Book{Dodge_encyclopedia_2008,
title = {The Concise Encyclopedia of Statistics},
author = {Yadolah Dodge},
publisher = {Springer},
year = {2007},
isbn = {ISBN 978-0-387-32833-1}
}
@article{doi:10.1080/10691898.2020.1787116,
author = {Mine Dogucu and Mine Çetinkaya-Rundel},
title = {Web Scraping in the Statistics and Data Science Curriculum: Challenges and Opportunities},
journal = {Journal of Statistics Education},
volume = {0},
number = {0},
pages = {1-11},
year = {2020},
publisher = {Taylor & Francis},
doi = {10.1080/10691898.2020.1787116},
URL = {
https://doi.org/10.1080/10691898.2020.1787116
},
eprint = {
https://doi.org/10.1080/10691898.2020.1787116
}
,
abstract = { Abstract: Best practices in statistics and data science courses include the use of real and relevant data as well as teaching the entire data science cycle starting with importing data. A rich source of real and current data is the web, where data are often presented and stored in a structure that needs some wrangling and transforming before they can be ready for analysis. The web is a resource students naturally turn to for finding data for data analysis projects, but without formal instruction on how to get that data into a structured format, they often resort to copy-pasting or manual entry into a spreadsheet, which are both time consuming and error-prone. Teaching web scraping provides an opportunity to bring such data into the curriculum in an effective and efficient way. In this article, we explain how web scraping works and how it can be implemented in a pedagogically sound and technically executable way at various levels of statistics and data science curricula. We provide classroom activities where we connect this modern computing technique with traditional statistical topics. Finally, we share the opportunities web scraping brings to the classrooms as well as the challenges to instructors and tips for avoiding them. }
}
@Book{Duarte_2008,
title = {slide:ology: the art and science of creating great presentations},
author = {Nancy Duarte},
publisher = {O'Reilly},
year = {2008},
isbn = {ISBN 978-0-596-52234-6},
url = {https://www.duarte.com/books/slideology/},
}
@online{EBC_PVL,
title = {Provincial Voters List},
author = {{Elections BC}},
date = {2020},
url = {https://elections.bc.ca/voting/voters-list/the-provincial-voters-list/},
note = {Accessed on 2020-08-01}
}
@techreport{EBC_Annual_201718,
title = {Annual Report 2017/18 and Service Plan 2018/19 - 2020/21},
author = {{Elections BC}},
date = {2018},
url = {https://elections.bc.ca/docs/rpt/AR1718SP1821.pdf},
note = {Accessed on 2020-08-01}
}
@Book{ElEmam_Arbuckle_2013,
title = {Anonymizing Health Data},
author = {Khaled El Emam and Luk Arbuckle},
publisher = {O'Reilly},
year = {2013},
isbn = {ISBN 9781449363079},
url = {https://www.oreilly.com/library/view/anonymizing-health-data/9781449363062/}
}
@article{Ellis_Leek_2017,
title = {How to Share Data for Collaboration},
author = {Sharon E. Ellis and Jeffrey T. Leek},
year = {2017},
journal = {The American Statistician},
volume = {72},
number = {1},
pages = {53-57},
DOI = {10.1080/00031305.2017.1375987},
url = {https://doi.org/10.1080/00031305.2017.1375987}
}
@techreport{ESS_datavalidation_2018,
title = {Methodology for data validation 2.0},
edition = {Revised Edition},
author = {{Eurostat}},
publisher = {{European Statistical System}},
year = {2018}
}
@Book{Evergreen_2014,
title = {Presenting Data Effectively: Communicating Your Findings for Maximum Impact},
author = {Stephanie D.H. Evergreen},
publisher = {Sage},
year = {2014},
isbn = {ISBN 978-1-4522-5736-5},
url = {https://us.sagepub.com/en-us/nam/presenting-data-effectively/book246124},
}
@article{tm,
title = {Text Mining Infrastructure in R},
author = {Ingo Feinerer and
Kurt Hornik and
David Meyer},
year = {2008},
journal = {Journal of Statistical Software},
volume = {25},
number = {5},
pages = {1-54},
url = {http://www.jstatsoft.org/v25/i05/}
}
@online{Ford_lubridate_2017,
author = {Clay Ford},
title = {Working with dates and time in R using the lubridate package},
year = {2017},
publisher = {University of Virginia Library. Research Data Services + Sciences.},
url = {https://data.library.virginia.edu/working-with-dates-and-time-in-r-using-the-lubridate-package/},
note = {Accessed: 2020-07-01}
}
@Book{Friendly_Meyer_2016,
title = {Discrete Data Analysis with R: Visualization and Modeling Techniques for Categorical and Count Data},
author = {Michael Friendly and
David Meyer},
publisher = {CRC Press},
year = {2016},
isbn = {ISBN 978-1-4987-2583-5},
}
@Book{Gandrud_2015,
title = {Reproducible Research with R and R Studio (Second Edition)},
author = {Christopher Gandrud},
publisher = {Chapman and Hall/CRC},
year = {2015},
isbn = {ISBN 9781498715379}
}
@article{@Gebru_et_al_datasheets,
title={Datasheets for Datasets},
author={Timnit Gebru and Jamie Morgenstern and Briana Vecchione and Jennifer Wortman Vaughan and Hanna Wallach and Hal Daumé III au2 and Kate Crawford},
year={2020},
eprint={1803.09010},
archivePrefix={arXiv},
primaryClass={cs.DB},
url={https://arxiv.org/abs/1803.09010}
}
@Book{Gelman_etal_2014,
title = {Bayesian Data Analysis (Third Edition)},
author = {Andrew Gelman, John B. Carlin,
Hal S. Stern, David B. Dunson,
Aki Vehtari, and Donald B. Rubin},
publisher = {CRC Press},
year = {2014},
isbn = {ISBN 978-1-4398-4095-5},
}
@Book{Gillespie_Lovelace_2017,
title = {Efficient R Programming: A Practical Guide to Smarter Programming},
author = {Colin Gillespie and Robin Lovelace},
publisher = {O'Reilly},
year = {2017},
isbn = {ISBN 978-1-491-95078-4},
url = {https://csgillespie.github.io/efficientR/}
}
@Book{Graham_etal_2015,
title = {Exploring Big Historical Data: The Historian's Macroscope},
author = {Shawn Graham, Ian Milligan,
and Scott Weingart},
publisher = {Imperial College Press},
year = {2015},
isbn = {ISBN 978-1-78326-637-1},
url = {http://www.themacroscope.org/2.0/}
}
@article{6700284420111201,
Abstract = {Rationale and objectives The availability of anonymized data is a keystone of medical research, yet little is known about lay views towards the process of anonymization or on the way that anonymized medical data are transferred to researchers. Methods During May and June 2009, as part of a wider consultation on methods for releasing data to researchers, three focus groups ( n = 19) were conducted exploring lay attitudes towards the traditional 'warehouse' model commonly used in medical research for delivering anonymized National Health Service (NHS) data to researchers. The focus groups explored different processes such as the copying of data, use of programmers for linkage and anonymization, the transfer of data and governance. Results The recognition of the positive aspects of medical research and desire to support it formed the context for discussions. Nonetheless, individuals varied in their attitudes to the use of anonymized data extracts for research from their health records},
Author = {Haddow, Gill and Bruce, Ann and Sathanandam, Shiva and Wyatt, Jeremy C.},
ISSN = {13561294},
Journal = {Journal of Evaluation in Clinical Practice},
Keywords = {FOCUS groups, INFORMED consent (Medical law), MEDICAL ethics, MEDICAL records, MEDICAL research, NATIONAL health services, PRIVACY, QUESTIONNAIRES, RESEARCH funding, RESEARCH ethics, SECURITY systems, TRUST, RESEARCH subjects (Persons), DESCRIPTIVE statistics, SCOTLAND, anonymized data, consent, lay views, warehouse model},
Number = {6},
Pages = {1140 - 1146},
Title = {'Nothing is really safe': a focus group study on the processes of anonymizing and sharing of health data for research purposes.},
Volume = {17},
URL = {http://ezproxy.library.uvic.ca/login?url=http://search.ebscohost.com/login.aspx?direct=true&db=aph&AN=67002844&site=ehost-live&scope=site},
Year = {2011},
}
@Book{Healy_2019,
title = {Data Visualization: A Practical Introduction},
author = {Kieran Healy},
publisher = {Princeton},
year = {2019},
isbn = {ISBN 978-0-691-18162-2},
url = {http://socviz.co/},
}
@Book{Hellerstein_etal_2017,
title = {Principles of Data Wrangling},
author = {Joseph M. Hellerstein and Tye Rattenbury and
Jeffrey Heer and Sean Kandel and Connor Carreras},
publisher = {O'Reilly},
year = {2017},
isbn = {ISBN 9781491938928},
url = {https://www.oreilly.com/library/view/principles-of-data/9781491938911/},
}
@article{Hicks_Peng_2019,
title = {Elements and Principles of Data Analysis},
author = {Stephanie C. Hicks and Roger D. Peng},
year = {2019},
journal = {arXiv.org},
volume = {},
number = {},
pages = {},
DOI = {},
url = {https://arxiv.org/abs/1903.07639v1}
}
@article{Hicks_Peng_2019b,
title = {Evaluating the Success of a Data Analysis},
author = {Stephanie C. Hicks and Roger D. Peng},
year = {2019},
journal = {arXiv.org},
volume = {},
number = {},
pages = {},
DOI = {},
url = {https://arxiv.org/abs/1904.11907}
}
@article{Hsieh_etal_2004,
title = {SARS epidemiology modeling},
author = {YH Hsieh, JY Lee, HL Chang},
year = {2004},
journal = {Emerging infectious diseases},
volume = {10},
number = {6},
pages = {1165–1168},
DOI = {10.3201/eid1006.031023},
url = {https://doi.org/10.3201/eid1006.031023}
}
@Book{Hundepool_etal_2012,
title = {Statistical Disclosure Control},
author = {Anco Hundepool and Josep Domingo-Ferrer and Luisa Franconi and
Sarah Giessing and Eric Schulte Nordholt and Keith Spicer and
Peter-Paul de Wolf},
publisher = {Wiley},
series = {Wiley Series in Survey Methodology},
year = {2012},
isbn = {ISBN: 978-0-470-37308-8},
url = {http://ca.wiley.com/WileyCDA/WileyTitle/productCd-1119978157.html},
}
@Book{Hvitfeldt_Silge_2020,
title = {Supervised Machine Learning for Text Analysis in R},
author = {Emil Hvitfeldt and
Julia Silge},
year = {2020},
url = {https://smltar.com/},
urldate = {2020-07-22},
note = {Accessed: 2020-07-27}
}
@Book{Hyndman_Athanasopoulos_2021,
author = {Rob J Hyndman and George Athanasopoulos},
title = {Forecasting: Principles and Practice},
edition = {Third},
publisher = {OTexts: Melbourne, Australia},
year = {2021},
url = {https://otexts.com/fpp3/},
}
@Book{Ismay_Kim_2018,
title = {Modern Dive: Statistical Inference via Data Science (A moderndive into R and the tidyverse)},
author = {Chester Ismay and
Albert Y. Kim},
publisher = {self-published},
year = {2019},
url = {https://moderndive.com/},
}
@Book{James_Witten_Hastie_Tibshirani_2014,
title = {An Introduction to Statistical Learning},
author = {Gareth James, Daniela Witten, Trevor Hastie, Robert Tibshirani},
publisher = {Springer},
year = {2014},
isbn = {ISBN 978-1-4614-7138-7},
url = {https://www.statlearning.com/},
}
@inproceedings{Kennedy_1997,
author = {Shawna Kennedy},
year = {1997},
title = {Options in Data Validation: Principles for Checking Analytical Data Quality},
journal = {WTQA '97–13th Annual Waste Testing & Quality Assurance Symposium},
url = {https://clu-in.org/download/char/dataquality/skennedy.pdf}
}
@Book{Kirk_2016,
title = {Data Visualisation: A Handbook for Data Driven Design},
author = {Andy Kirk},
publisher = {Sage},
year = {2016},
isbn = {ISBN 978-1-4739-1213-7},
}
@Book{Kline_SQL_2009,
title = {SQL in a Nutshell},
edition = 3,
author = {Kevin E. Kline and Daniel Kline and Brand Hunt},
publisher = {O’Reilly Media},
year = {2009},
isbn = {ISBN 978-0-596-51884-4},
}
@article{Knuth_1984,
title = {Literate Programming},
author = {Donald E. Knuth},
year = {1984},
journal = {The Computer Journal},
volume = {27},
number = {2},
pages = {97-111},
DOI = {doi.org/10.1093/comjnl/27.2.97},
url = {https://doi.org/10.1093/comjnl/27.2.97}
}
@online{Kosara_pair_of_pies_2016,
author = {Robert Kosara},
title = {A Pair of Pie Chart Papers},
year = {2016},
url = {https://eagereyes.org/papers/a-pair-of-pie-chart-papers},
note = {Accessed: 2020-05-20}
}
@online{Kosara_pie_2016,
author = {Robert Kosara},
title = {An Illustrated Tour of the Pie Chart Study Results},
year = {2016},
url = {https://eagereyes.org/blog/2016/an-illustrated-tour-of-the-pie-chart-study-results},
note = {Accessed: 2020-05-20}
}
@inproceedings{Kundra_2010,
author = {Vitek Kundra},
title = {Testimony of Vitek Kundra},
publisher = {United States. Senate. One Hundred Eleventh Congress. Committee on Homeland Security & Governmental Affairs. Federal Financial Management, Government Information, Federal Services, & International Security Subcommittee},
booktitle = {"Removing the Shroud of Secrecy: Making Government More Transparent and Accountable--Parts I and {II}, March 23, 2010"},
url = {https://www.govinfo.gov/content/pkg/CHRG-111shrg56893/html/CHRG-111shrg56893.htm},
date = {2010}
}
@article{Larkin_Simon_1987,
author = {Larkin, Jill H. and Simon, Herbert A.},
title = {Why a Diagram is (Sometimes) Worth Ten Thousand Words},
journal = {Cognitive Science},
volume = {11},
number = {1},
pages = {65-100},
doi = {10.1111/j.1551-6708.1987.tb00863.x},
url = {https://onlinelibrary.wiley.com/doi/abs/10.1111/j.1551-6708.1987.tb00863.x},
eprint = {https://onlinelibrary.wiley.com/doi/pdf/10.1111/j.1551-6708.1987.tb00863.x},
abstract = {We distinguish diagrammatic from sentential paper-and-pencil representations of information by developing alternative models of information-processing systems that are informationally equivalent and that can be characterized as sentential or diagrammatic. Sentential representations are sequential, like the propositions in a text. Diagrammatic representations are indexed by location in a plane. Diagrammatic representations also typically display information that is only implicit in sentential representations and that therefore has to be computed, sometimes at great cost, to make it explicit for use. We then contrast the computational efficiency of these representations for solving several illustrative problems in mathematics and physics. When two representations are informationally equivalent, their computational efficiency depends on the information-processing operators that act on them. Two sets of operators may differ in their capabilities for recognizing patterns, in the inferences they can carry out directly, and in their control strategies (in particular, the control of search). Diagrammatic and sentential representations support operators that differ in all of these respects. Operators working on one representation may recognize features readily or make inferences directly that are difficult to realize in the other representation. Most important, however, are differences in the efficiency of search for information and in the explicitness of information. In the representations we call diagrammatic, information is organized by location, and often much of the information needed to make an inference is present and explicit at a single location. In addition, cues to the next logical step in the problem may be present at an adjacent location. Therefore problem solving can proceed through a smooth traversal of the diagram, and may require very little search or computation of elements that had been implicit.},
year = {1987}
}
@article{doi:10.1287/isre.2016.0676,
author = {Li, Xiao-Bai and Qin, Jialun},
title = {Anonymizing and Sharing Medical Text Records},
journal = {Information Systems Research},
volume = {28},
number = {2},
pages = {332-352},
year = {2017},
doi = {10.1287/isre.2016.0676},
URL = {
https://doi.org/10.1287/isre.2016.0676
},
eprint = {
https://doi.org/10.1287/isre.2016.0676
}
,
abstract = { Health information technology has increased accessibility of health and medical data and benefited medical research and healthcare management. However, there are rising concerns about patient privacy in sharing medical and healthcare data. A large amount of these data are in free text form. Existing techniques for privacy-preserving data sharing deal largely with structured data. Current privacy approaches for medical text data focus on detection and removal of patient identifiers from the data, which may be inadequate for protecting privacy or preserving data quality. We propose a new systematic approach to extract, cluster, and anonymize medical text records. Our approach integrates methods developed in both data privacy and health informatics fields. The key novel elements of our approach include a recursive partitioning method to cluster medical text records based on the similarity of the health and medical information and a value-enumeration method to anonymize potentially identifying information in the text data. An experimental study is conducted using real-world medical documents. The results of the experiments demonstrate the effectiveness of the proposed approach. }
}
@Book{Long_Teetor_2019,
title = {R Cookbook, 2nd Edition},
author = {James (JD) Long and Paul Teetor},
publisher = {O'Reilly},
year = {2019},
isbn = {ISBN 978-1492040682},
url = {https://rc2e.com/},
}
@online{Lowndes_Horst_tidy_data2020,
author = {Julie Lowndes and Allison Horst},
title = {Tidy Data for Efficiency, Reproducibility, and Collaboration},
year = {2020},
url = {https://www.openscapes.org/blog/2020/10/12/tidy-data/},
note = {Accessed: 2021-03-14}
}
@Book{Malik_Goldwasser_Johnston_2019,
title = {{SQL} for Data Analytics: Perform fast and efficient data analysis with the power of {SQL}},
author = {Upom Malik and Matt Goldwasser and Benjamin Johnston},
publisher = {Packt Publishing},
year = {2019},
isbn = {ISBN: 978-1789807356},
url = {https://www.packtpub.com/big-data-and-business-intelligence/sql-data-analysis},
}
@Book{Malik_Goldwasser_Johnston_2020,
title = {The Applied {SQL} Data Analytics Workshop},
edition = 2,
author = {Upom Malik and Matt Goldwasser and Benjamin Johnston},
publisher = {Packt Publishing},
year = {2020},
isbn = {ISBN: 978-1-80020-367-9},
url = {https://www.packtpub.com/data/the-applied-sql-data-analytics-workshop-second-edition},
}
@article {Matthews_etal_2017,
author = "Gregory J. Matthews and Pétala Gardênia da Silva Estrela Tuy and Robert K. Arthur",
title = "An examination of statistical disclosure issues related to publication of aggregate statistics in the presence of a known subset of the dataset using Baseball Hall of Fame ballots",
journal = "Journal of Quantitative Analysis in Sports",
year = "2017",
publisher = "De Gruyter",
address = "Berlin, Boston",
volume = "13",
number = "1",
doi = "https://doi.org/10.1515/jqas-2016-0085",
pages= "1 - 10",
url = "https://www.degruyter.com/view/journals/jqas/13/1/article-p1.xml"
}
@Book{McCallum_2012,
title = {Bad Data Handbook: Cleaning Up The Data So You Can Get Back To Work},
author = {O. Ethan McCallum},
publisher = {O'Reilly},
year = {2012},
isbn = {ISBN 9781449321888}
}
@online{McDermott_BDE_2020,
title = {Big Data In Economics (EC 410/510) - Lecture Material},
author = {Grant R. McDermott},
publisher = {Big Data in Economics—EC510 Lectures},
date = {2020},
url = {https://github.com/uo-ec510-2020-spring/lectures},
note = {https://raw.githack.com/uo-ec510-2020-spring/lectures/master/07-web-css/07-web-css.html},
note = {Accessed: 2020-09-10}
}
@Book{McElreath_2016,
title = {Statistical Rethinking: A Bayesian Course with Examples in R and Stan},
author = {Richard McElreath},
publisher = {CRC Press},
year = {2016},
isbn = {ISBN 978-1-4822-5344-3},
}
@article{McNamara_2018,
title = {Wrangling Categorical Data in R},
author = {Amelia McNamara},
year = {2018},
journal = {The American Statistician},
volume = {72},
number = {1},
pages = {97-104},
DOI = {10.1080/00031305.2017.1356375},
url = {https://www.tandfonline.com/doi/abs/10.1080/00031305.1973.10478966}
}
@online{McNulty_2020,
title = {Five Tidyverse Tricks You May Not Know About},
author = {Keith McNulty},
publisher = {towardsdatascience.com},
date = {2020},
url = {https://towardsdatascience.com/five-tidyverse-tricks-you-may-not-know-about-c5026d5a19da},
urldate = {2020-07-16},
note = {Accessed: 2020-07-16}
}
@online{Monkman_bird_2019,
author = {Martin Monkman},
title = {Same name, different bird},
year = {2019},
url = {https://martinmonkman.com/post/2019-06-02_same-name/},
note = {Accessed: 2020-05-19}
}
@online{Monroe_business_2018,
author = {Jeffrey Monroe},
title = {Business Analytics with R},
year = {2018},
url = {https://bookdown.org/jeffreytmonroe/business_analytics_with_r7/},
note = {Accessed: 2020-05-19}
}
@article{Muller_Freytag_problems_2003,
author = {Müller, Heiko and Freytag, Johann-Christoph},
year = {2003},
month = {01},
pages = {},
title = {Problems, methods, and challenges in comprehensive data cleansing},
url = {https://tarjomefa.com/wp-content/uploads/2015/06/3229-English.pdf}
}
@book{Murrell_data_technologies,
title = {Introduction to Data Technologies},
author = {Paul Murrell},
date = {2009},
isbn = {ISBN: 9781420065183},
publisher = {Chapman and Hall/CRC}
}
@incollection{Murrell_consumption,
title = {Data Intended for Human Consumption, Not Machine Consumption},
author = {Paul Murrell},
chapter = {3},
pages = {31–51},
booktitle = {Bad Data Handbook},
editor = {Q. Ethan McCallum},
date = {2013},
isbn = {ISBN: 978-1-449-32188-8},
publisher = {O'Reilly}
}
@Book{Navarro_learning_statistics,
title = {Learning statistics with R: A tutorial for psychology students and other beginners},
author = {Danielle Navarro},
year = {2019},
publisher = {self-published},
version = {0.6.1},
url = {https://learningstatisticswithr.com/book/},
note = {Accessed: 2021-04-16}
}
@Book{Nield_2016,
title = {Getting Started with {SQL}: A Hands-on Approach for Beginners},
author = {Thomas Nield},
publisher = {O'Reilly Media},
year = {2016},
isbn = {ISBN: 9781491938614},
url = {https://www.oreilly.com/library/view/getting-started-with/9781491938607/},
}
@Book{NussbaumerKnaflic_2015,
title = {Storytelling with data: a data visualization guide for business professionals},
author = {Cole Nussbaumer Knaflic},
publisher = {Wiley},
year = {2015},
isbn = {ISBN 9781119002253},
url = {https://www.storytellingwithdata.com/},
}
@techreport{ONS_guidelines_statistical_quality,
title = {Guidelines for measuring statistical quality},
author = {{Office for National Statistics}},
publisher = {National Statistics (UK)},
date = {2007},
urldate = {2020-01-08},
url = {https://unstats.un.org/unsd/dnss/docs-nqaf/UK-Guidelines_Subject.pdf},