References

Alberani, D. 2014. IMDbPY.

Albert, James, Max Marchi, and Benjamin S. Baumer. 2018. Analyzing Baseball Data with R. 2nd ed. CRC Press: Boca Raton, FL. https://www.crcpress.com/Analyzing-Baseball-Data-with-R-Second-Edition/Marchi-Albert-Baumer/p/book/9780815353515.

Albert, Jim. 2003. Teaching Statistics Using Baseball. Mathematical Association of America: Washington, DC.

Albert, Jim, and Jingchen Hu. 2019. Probability and Bayesian Modeling. CRC Press.

Allaire, J. J., J. Horner, V. Marti, and N. Porte. 2014. Markdown: Markdown Rendering for r. http://CRAN.R-project.org/package=markdown.

American Statistical Association Undergraduate Guidelines Workgroup. 2014. 2014 Curriculum Guidelines for Undergraduate Programs in Statistical Science. American Statistical Association.

Angwin, Julia, Jeff Larson, Surya Mattu, and Lauren Kirchner. 2016. Machine Bias. ProPublica.

Arnold, Jeffrey B. 2019. ggthemes: Extra Themes, Scales and Geoms for ggplot2. http://CRAN.R-project.org/package=ggthemes.

Ball, Richard, and Norm Medeiros. 2012. “Teaching Integrity in Empirical Research: A Protocol for Documenting Data Management and Analysis.” The Journal of Economic Education 43 (2): 182–89.

Barabási, A.-L., and R. Albert. 1999. “Emergence of Scaling in Random Networks.” Science 286 (5439): 509–12.

Barabási, A.-L., and J. Frangos. 2014. Linked: The New Science of Networks. Basic Books: New York.

Basu, Prithwish, Ben S. Baumer, Amotz Bar-Noy, Chi-Kin Chau, and Masdar City. 2015. “Social-Communication Composite Networks.” Chap. 1 in Opportunistic Mobile Social Networks, edited by Jie Wu and Yunsheng Wang. CRC Press: Boca Raton.

Baumer, B. S. 2015. “A Data Science Course for Undergraduates: Thinking with Data.” The American Statistician 69 (4): 334–42. https://doi.org/10.1080/00031305.2015.1081105.

Baumer, B. S., M. Çetinkaya-Rundel, A. Bray, L. Loi, and N. J. Horton. 2014. “R Markdown: Integrating a Reproducible Analysis Tool into Introductory Statistics.” Technology Innovations in Statistics Education 8 (1).

Baumer, B. S., and A. Zimbalist. 2014. The Sabermetric Revolution: Assessing the Growth of Analytics in Baseball. University of Pennsylvania Press: Philadelphia, PA.

Baumer, Ben. 2015. “In a Moneyball world, a Number of Teams Remain Slow to Buy into Sabermetrics.” In The Great Analytics Rankings, edited by Royce Webb. ESPN.com; ESPN.com.

Baumer, Ben S., George Rabanca, Amotz Bar-Noy, and Prithwish Basu. 2015. “Star Search: Effective Subgroups in Collaborative Social Networks.” In Proceedings of the 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2015, Paris, France, August 25–28, 2015, edited by Jian Pei, Fabrizio Silvestri, and Jie Tang. ACM. https://doi.org/10.1145/2808797.2810062.

Baumer, Ben, Prithwish Basu, and Amotz Bar-Noy. 2011. “Modeling and Analysis of Composite Network Embeddings.” In MSWiM, edited by Ahmed Helmy, Björn Landfeldt, and Luciano Bononi. ACM.

Baumer, Benjamin S., Randi L. Garcia, Albert Y. Kim, Katherine M. Kinnaird, and Miles Q. Ott. 2022. “Integrating Data Science Ethics Into an Undergraduate Major: A Case Study.” Journal of Statistics and Data Science Education 30 (1): 15–28. https://doi.org/10.1080/26939169.2022.2038041.

Baumer, Benjamin S., Yijin Wei, and Gary S. Bloom. 2016. “The Smallest Non-Autograph.” Discussiones Mathematicae Graph Theory 36 (3): 577–602. https://doi.org/10.7151/dmgt.1881.

Beckman, Matthew D., Mine Çetinkaya-Rundel, Nicholas J. Horton, Colin W. Rundel, Adam J. Sullivan, and Maria Tackett. 2021. “Implementing Version Control with Git and GitHub as a Learning Objective in Statistics and Data Science Courses.” Journal of Statistics and Data Science Education 29 (sup1): S132–44. https://doi.org/10.1080/10691898.2020.1848485.

Belle, G. van. 2008. Statistical Rules of Thumb (Second Edition). John Wiley & Sons: Hoboken, NJ.

Bivand, Roger S, Edzer Pebesma, and Virgilio Gómez-Rubio. 2013. Applied Spatial Data Analysis with r (Second Edition). Springer Verlag: New York, NY. http://www.asdar-book.org/.

Bogdanov, Petko, Ben S. Baumer, Prithwish Basu, Amotz Bar-Noy, and Ambuj K. Singh. 2013. “As Strong as the Weakest Link: Mining Diverse Cliques in Weighted Graphs.” In Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2013, Prague, Czech Republic, September 23–27, 2013, Proceedings, Part I, edited by Hendrik Blockeel, Kristian Kersting, Siegfried Nijssen, and Filip Zelezný, vol. 8188. Lecture Notes in Computer Science. Springer Verlag: New York, NY. https://doi.org/10.1007/978-3-642-40988-2_34.

Bombardier, C., L. Laine, A. Reicin, et al. 2000. “Comparison of Upper Gastrointestinal Toxicity of Rofecoxib and Naproxen in Patients with Rheumatoid Arthritis.” New England Journal of Medicine 343: 1520–28.

Breiman, Leo. 2001. “Statistical Modeling: The Two Cultures.” Statistical Science 16 (3): 199–215.

Brewer, C. A. 1994. “Color Use Guidelines for Mapping and Visualization.” Visualization in Modern Cartography 2: 123–48.

Brewer, C. A. 1999. “Color Use Guidelines for Data Representation.” Proceedings of the Section on Statistical Graphics, American Statistical Association, 55–60.

Bridgeford, Lydell C. 2014. Q&A: Statistical Proof of Discrimination Isn’t Static.

Broman, Karl W., and Kara H. Woo. 2018. “Data Organization in Spreadsheets.” The American Statistician 72 (1): 2–10. https://doi.org/10.1080/00031305.2017.1375989.

Bryan, Jennifer, the STAT 545 TAs, and Jim Hester. 2018. Happy Git and GitHub for the useR. GitHub. https://happygitwithr.com/.

Cannon, Ann R, George W Cobb, Bradley A Hartlaub, et al. 2019. STAT2: Building Models for a World of Data (Second Edition). W. H. Freeman; Company: New York, NY.

CERN. 2008. LHC Guide: A Collection of Facts and Figures about the Large Hadron Collider (LHC) in the Form of Questions and Answers. CERN.

Çetinkaya-Rundel, M., and Johanna Hardin. 2021. Introduction to Modern Statistics. OpenIntro.org.

Çetinkaya-Rundel, Mine, Johanna Hardin, Benjamin S. Baumer, Amelia McNamara, Nicholas J. Horton, and Colin W. Rundel. 2022. “An Educator’s Perspective of the Tidyverse.” Technology Innovations in Statistics Education. https://escholarship.org/uc/item/7kk4d922.

Chamandy, N., O. Muraldharan, and S. Wager. 2015. “Teaching Statistics at ‘Google-Scale’.” The American Statistician 69 (4): 283–91.

Cleveland, W. S. 2001. “Data Science: An Action Plan for Expanding the Technical Areas of the Field of Statistics.” International Statistical Review 69 (1): 21–26.

Cleveland, W. S., and R. McGill. 1984. “Graphical Perception: Theory, Experimentation, and Application to the Development of Graphical Methods.” Journal of the American Statistical Association 79 (387): 531–54.

Cobb, George W. 2007. “The Introductory Statistics Course: A Ptolemaic Curriculum?” Technology Innovations in Statistics Education (TISE) 1 (1).

Cobb, George W. 2015. “Mere Renovation Is Too Little Too Late: We Need to Rethink Our Undergraduate Curriculum from the Ground Up.” The American Statistician 69 (4): 266–82.

Columbus, Louis. 2019. Data Scientist Leads 50 Best Jobs in America for 2019 According to Glassdoor. Forbes.com.

Committee on Professional Ethics. 1999. Ethical Guidelines for Statistical Practice. American Statistical Association.

Cook, R. D. 1982. Residuals and Influence in Regression. Chapman & Hall, London.

Cressie, N. 1993. Statistics for Spatial Data. John Wiley & Sons: Hoboken, NJ.

D’Ignazio, Catherine, and Lauren F. Klein. 2020. Data Feminism. MIT Press: Cambridge, MA. https://datafeminism.io.

De Veaux, Richard D, Mahesh Agarwal, Maia Averett, et al. 2017. “Curriculum Guidelines for Undergraduate Programs in Data Science.” Annual Review of Statistics and Its Application 4: 15–30. https://doi.org/10.1146/annurev-statistics-060116-053930.

Diez, D. M., C. D. Barr, and M. Çetinkaya-Rundel. 2019. OpenIntro Statistics (Fourth Edition). OpenIntro.org.

Donoho, David. 2017. “50 Years of Data Science.” Journal of Computational and Graphical Statistics 26 (4): 745–66. https://doi.org/10.1080/10618600.2017.1384734.

Easley, David, and Jon Kleinberg. 2010. Networks, Crowds, and Markets: Reasoning about a Highly Connected World. Cambridge University Press: Cambridge, UK.

Editorial. 2013. “Announcement: Reducing Our Irreproducibility.” Nature 496. https://doi.org/doi:10.1038/496398a.

Efron, Bradley. 2020. “Prediction, Estimation, and Attribution.” Journal of the American Statistical Association 115 (530): 636–55.

Efron, Bradley, and Trevor Hastie. 2016. Computer Age Statistical Inference: Algorithms, Evidence, and Data Science. Cambridge University Press: Cambridge, UK.

Efron, B., and R. J. Tibshirani. 1993. An Introduction to the Bootstrap. Chapman & Hall: London.

Ellenberg, Jonas H. 1983. “Ethical Guidelines for Statistical Practice: A Historical Perspective.” The American Statistician 37 (1): 1–4.

Engel, Claudia A. 2019. R for Geospatial Analysis and Mapping. The Geographic Information Science & Technology Body of Knowledge. https://doi.org/10.22224/gistbok/2019.1.3.

Engstrom, Richard L, and John K Wildgen. 1977. “Pruning Thorns from the Thicket: An Empirical Test of the Existence of Racial Gerrymandering.” Legislative Studies Quarterly, 465–79.

Erdős, P., and A. Rényi. 1959. “On Random Graphs.” Publicationes Mathematicae Debrecen 6: 290–97.

Euler, Leonhard. 1953. “Leonhard Euler and the Königsberg Bridges.” Scientific American 189 (1): 66–70.

Finzer, W. 2013. “The Data Science Education Dilemma.” Technology Innovations in Statistics Education 7 (2).

Fox, J. 2009. “Aspects of the Social Organization and Trajectory of the R Project.” The R Journal 1 (2): 5–13. http://journal.r-project.org/archive/2009-2/RJournal_2009-2_Fox.pdf.

Futschek, Gerald. 2006. “Algorithmic Thinking: The Key for Understanding Computer Science.” International Conference on Informatics in Secondary Schools-Evolution and Perspectives, 159–68.

Gandrud, C. 2014. Reproducible Research with R and RStudio. CRC Press: Boca Raton, FL.

Garey, Michael R, and David S Johnson. 1979. Computers and Intractability: A Guide to the Theory of NP-Completeness. W. H. Freeman; Company: New York, NY.

Garnier, Simon. 2024. Viridis: Colorblind-Friendly Color Maps for r. https://sjmgarnier.github.io/viridis/.

Garnier, Simon. 2026. viridisLite: Colorblind-Friendly Color Maps (Lite Version). https://sjmgarnier.github.io/viridisLite/.

Gelman, Andrew. 2011. “Ethics and Statistics: Open Data and Open Methods.” Chance 24 (4): 51–53.

Gelman, Andrew. 2012. “Ethics and Statistics: Ethics and the Statistical Use of Prior Information.” Chance 25 (4): 52–54.

Gelman, Andrew. 2020. “Ethics and Statistics: Statistics as Squid Ink.” Chance 33 (2): 25–27.

Gelman, Andrew, Jeffrey Fagan, and Alex Kiss. 2007. “An Analysis of the New York City Police Department’s “Stop-and-Frisk" Policy in the Context of Claims of Racial Bias.” Journal of the American Statistical Association 102 (479): 813–23. https://doi.org/10.1198/016214506000001040.

Gelman, Andrew, and Eric Loken. 2012. “Ethics and Statistics: Statisticians: When We Teach, We Don’t Practice What We Preach.” Chance 25 (1): 47–48.

Gelman, Andrew, and Aki Vehtari. 2021. “What Are the Most Important Statistical Ideas of the Past 50 Years?” Journal of the American Statistical Association 116 (536): 2087–97. https://doi.org/10.1080/01621459.2021.1938081.

Gelman, A., C. Pasarica, and R. Dodhia. 2002. “Let’s Practice What We Preach: Turning Tables into Graphs.” The American Statistician 56 (2): 121–30.

Glickman, Mark, Jason Brown, and Ryan Song. 2019. “(A) Data in the Life: Authorship Attribution in Lennon-McCartney Songs.” Harvard Data Science Review 1 (1). https://doi.org/10.1162/99608f92.130f856e.

Good, Phillip I, and James W Hardin. 2012. Common Errors in Statistics (and How to Avoid Them). John Wiley & Sons: Hoboken, NJ.

Graphodatsky, Alexander S, Vladimir A Trifonov, and Roscoe Stanyon. 2011. “The Genome Diversity and Karyotype Evolution of Mammals.” Molecular Cytogenetics 4 (1): 1.

Green, J. L., and E. E. Blankenship. 2015. “Fostering Conceptual Understanding in Mathematical Statistics.” The American Statistician 69 (4): 315–25.

Hardin, J., R. Hoerl, N. J. Horton, et al. 2015. “Data Science in Statistics Curricula: Preparing Students to ’Think with Data’.” The American Statistician 69 (4): 343–53.

Hastie, Trevor, Robert Tibshirani, and J Jerome H Friedman. 2009. The Elements of Statistical Learning. 2nd ed. Springer Verlag: New York, NY.

Henry, Lionel. 2020. Interactivity and Programming in the Tidyverse. RStudio::conf 2020. https://rstudio.com/resources/rstudioconf-2020/interactivity-and-programming-in-the-tidyverse/.

Herndon, Thomas, Michael Ash, and Robert Pollin. 2014. “Does High Public Debt Consistently Stifle Economic Growth? A Critique of Reinhart and Rogoff.” Cambridge Journal of Economics 38 (2): 257–79. https://umassmed.edu/uploadedFiles/QHS/Camb.%20J.%20Econ.-2013-Herndon-cje-bet075.pdf.

Hesterberg, T. 2015. “What Teachers Should Know about the Bootstrap: Resampling in the Undergraduate Statistics Curriculum.” The American Statistician 69 (4): 371–86.

Hesterberg, T. C., D. S. Moore, S. Monaghan, A. Clipson, and R. Epstein. 2005. Bootstrap Methods and Permutation Tests. W. H. Freeman; Company: New York, NY. http://bcs.whfreeman.com/ips5e/content/cat_080/pdf/moore14.pdf.

Hoaglin, David C. 2016. “Regressions Are Commonly Misinterpreted.” Stata Journal 16 (1): 5–22.

Hodge, Jonathan K, Emily Marshall, and Geoff Patterson. 2010. “Gerrymandering and Convexity.” The College Mathematics Journal 41 (4): 312–24.

Horton, N. J. 2013. “I Hear, I Forget. I Do, I Understand: A Modified Moore-Method Mathematical Statistics Course.” The American Statistician 67 (3): 219–28.

Horton, N. J. 2015. “Challenges and Opportunities for Statistics and Statistical Education: Looking Back, Looking Forward.” The American Statistician 69 (2): 138–45.

Horton, N. J., B. S. Baumer, and H. Wickham. 2015. “Setting the Stage for Data Science: Integration of Data Management Skills in Introductory and Second Courses in Statistics.” Chance 28 (2).

Horton, N. J., E. R. Brown, and L. Qian. 2004. “Use of R as a Toolbox for Mathematical Statistics Exploration.” The American Statistician 58 (4): 343–57.

Horton, N. J., and J. S. Hardin. 2015. “Teaching the Next Generation of Statistics Students to “Think with Data": Special Issue on Statistics and the Undergraduate Curriculum.” The American Statistician 69 (4): 259–65.

Horton, N. J., and K. P. Kleinman. 2007. “Much Ado about Nothing: A Comparison ofmissing Data Methods and Software to Fit Incomplete Data Regression Models.” The American Statistician 61: 79–90.

Horton, Nicholas J., Rohan Alexander, Micaela Parker, Aneta Piekut, and Colin Rundel. 2022. “The Growing Importance of Reproducibility and Responsible Workflow in the Data Science and Statistics Curriculum.” Journal of Statistics and Data Science Education 30 (3): 207–8. https://doi.org/10.1080/26939169.2022.2141001.

Howe, Bill. 2014. Data Manipulation at Scale: Systems and Algorithms. University of Washington; Coursera. https://www.coursera.org/learn/data-manipulation.

Hubert, Lawrence, and Howard Wainer. 2012. A Statistical Guide for the Ethically Perplexed. CRC Press: Boca Raton, FL.

Huff, Darrell. 1954. How to Lie with Statistics. W.W. Norton & Company: New York, NY.

Hyafil, Laurent, and Ronald L Rivest. 1976. “Constructing Optimal Binary Decision Trees Is NP-Complete.” Information Processing Letters 5 (1): 15–17.

Ihaka, R., and R. Gentleman. 1996. “R: A Language for Data Analysis and Graphics.” Journal of Computational and Graphical Statistics 5 (3): 299–314.

Imai, Kosuke, and Kabir Khanna. 2016. “Improving Ecological Inference by Predicting Individual Ethnicity from Voter Registration Records.” Political Analysis, 263–72. https://doi.org/10.1093/pan/mpw001.

IMDB.com. 2013. Internet Movie Database.

Ioannidis, John PA. 2005. “Why Most Published Research Findings Are False.” Chance 18 (4): 40–47.

James, B. 1986. The Bill James Historical Baseball Abstract. Random House: New York, NY.

James, Gareth, Daniela Witten, Trevor Hastie, and Robert Tibshirani. 2013. An Introduction to Statistical Learning. Springer Verlag: New York, NY.

Kern, Silke, Ingmar Skoog, Anne Börjesson-Hanson, et al. 2013. “Retraction Notice to “Lower CSF Interleukin-6 Predicts Future Depression in a Population-Based Sample of Older Women Followed for 17 Years".” Brain, Behavior, and Immunity 32: 153–58.

Kern, Silke, Ingmar Skoog, Anne Börjesson-Hanson, et al. 2014. “Higher CSF Interleukin-6 and CSF Interleukin-8 in Current Depression in Older Women. Results from a Population-Based Sample.” Brain, Behavior, and Immunity 41: 55–58.

Kim, Albert Y, and Adriana Escobedo-Land. 2015. “OkCupid Data for Introductory Statistics and Data Science Courses.” Journal of Statistics Education 23 (2). https://doi.org/10.1080/10691898.2015.11889737.

Kirkegaard, Emil OW, and Julius D Bjerrekær. 2016. “The OKCupid Dataset: A Very Large Public Dataset of Dating Site Users.” Open Differential Psychology 46: 1–10.

Kline, K. E, D. Kline, B. Hunt, and D. Heymann-Reder. 2008. SQL in a Nutshell. O’Reilly Media: Sebastopol, CA.

Knuth, D. 1992. “Literate Programming.” CSLI Lecture Notes, Stanford University 27.

Kuhn, Max. 2020. CRAN Task View: Reproducible Research. https://CRAN.R-project.org/view=ReproducibleResearch.

Kuiper, Shonda, and Jeff Sklar. 2012. Practicing Statistics: Guided Investigations for the Second Course. Pearson Education: New York, NY.

Laney, D. 2001. “3D Data Management: Controlling Data Volume, Velocity and Variety.” META Group Research Note 6: 70.

Lewis, M. 2003. Moneyball: The Art of Winning an Unfair Game. W.W. Norton & Company: New York, NY.

Little, R J A, and D B Rubin. 2002. Statistical Analysis with Missing Data (Second Edition). John Wiley & Sons: Hoboken, NJ.

Lovelace, Robin, Jakub Nowosad, and Jannes Muenchow. 2019. Geocomputation with R. CRC Press: Boca Raton, FL. https://geocompr.robinlovelace.net/.

Ludwig, Lew. 2012. Technically Speaking.

Lunzer, Aran, and Amelia McNamara. 2017. Introduction to the "Exploring Histograms" Online Essay. Viewpoints Research Institute. http://www.vpri.org/pdf/rn2017003_histogram-intro.pdf.

Mackenzie, John. 2009. Gerrymandering and Legislator Efficiency. University of Delaware. https://www.udel.edu/johnmack/research/gerrymandering.pdf.

Marchi, M., and J. Albert. 2013. Analyzing Baseball Data with r. CRC Press: Boca Raton, FL.

McCallum, E., and S. Weston. 2011. Parallel r. O’Reilly Media: Sebastopol, CA.

Mosteller, F. 1987. Fifty Challenging Problems in Probability with Solutions. Dover Publications: Mineola, NY.

Mosteller, Frederick, and David L Wallace. 1963. “Inference in an Authorship Problem: A Comparative Study of Discrimination Methods Applied to the Authorship of the Disputed Federalist Papers.” Journal of the American Statistical Association 58 (302): 275–309.

National Academies of Science, Engineering, and Medicine. 2018. Data Science for Undergraduates: Opportunities and Options. National Academies. https://nas.edu/envisioningds.

National Academies of Science, Engineering, and Medicine. 2019. Reproducibility and Replicability in Science. National Academies. https://doi.org/10.17226/25303.

Nielsen, Finn Årup. 2011. “A New ANEW: Evaluation of a Word List for Sentiment Analysis in Microblogs.” CoRR abs/1103.2903. http://arxiv.org/abs/1103.2903.

Niemi, Richard G, Bernard Grofman, Carl Carlucci, and Thomas Hofeller. 1990. “Measuring Compactness and the Role of a Compactness Standard in a Test for Partisan and Racial Gerrymandering.” The Journal of Politics 52 (4): 1155–81.

Nolan, Deborah, and Duncan Temple Lang. 2010. “Computing in the Statistics Curricula.” The American Statistician 64 (2): 97–107. https://doi.org/10.1198/tast.2010.09132.

Nolan, D., and J. Perrett. 2016. “Teaching and Learning Data Visualization: Ideas and Assignments.” The American Statistician 70 (3): 260–69.

Nolan, D., and T. P. Speed. 1999. “Teaching Statistics Theory Through Applications.” The American Statistician 53: 370–75.

Nuzzo, R. 2014. “Scientific method: Statistical errors.” Nature 506: 150–52.

O’Neil, C. 2016. Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy. Crown Publishing, New York, NY.

Ohm, Paul. 2010. “Broken Promises of Privacy: Responding to the Surprising Failure of Anonymization.” UCLA Law Review 57: 1701. http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1450006.

Olford, R. W., and W. H. Cherry. 2003. Picturing Probability: The Poverty of Venn Diagrams, the Richness of Eikosograms. Unpublished manuscript.

Page, Lawrence, Sergey Brin, Rajeev Motwani, and Terry Winograd. 1999. The PageRank Citation Ranking: Bringing Order to the Web. Stanford University InfoLab.

Pierson, S. 2016. “Jordan Urges Both Computational and Inferential Thinking in Data Science.” Amstat News.

Provost, F., and T. Fawcett. 2013. “Data Science and Its Relationship to Big Data and Data-Driven Decision Making.” Big Data 1 (1): 51–59.

Pruim, Randall, Maria-Cristiana Gîrjău, and Nicholas Jon Horton. 2023. “Fostering Better Coding Practices for Data Scientists.” Harvard Data Science Review 5 (3). https://doi.org/10.1162/99608f92.97c9f60f.

R Core Team. 2020. R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing. https://www.R-project.org/.

Raghunathan, T. E. 2004. “What Do We Do with Missing Data? Some Options for Analysis of Incomplete Data.” Annual Review of Public Health 25: 99–117.

Ram, K., and H. Wickham. 2018. Wesanderson: A Wes Anderson Palette Generator. http://CRAN.R-project.org/package=wesanderson.

Rice, J. A. 2006. Mathematical Statistics and Data Analysis (Third Edition). Cengage Learning: Boston, MA.

Rizzo, M. L. 2019. Statistical Computing with R (Second Edition). CRC Press: Boca Raton, FL.

Rogoff, Kenneth, and Carmen Reinhart. 2010. “Growth in a Time of Debt.” American Economic Review 100 (2): 573–78. http://www.nber.org/papers/w15639.

Romano, J. P., and A. F. Siegel. 1986. Counterexamples in Probability and Statistics. Cengage Learning: Boston, MA.

Roose, Kevin. 2013. Meet the 28-Year-Old Grad Student Who Just Shook the Global Austerity Movement. New York Magazine. http://nymag.com/daily/intelligencer/2013/04/grad-student-who-shook-global-austerity-movement.html.

Rosling, O., A. R. Rönnlund, and H. Rosling. 2005. Gapminder. Gapminder.org. https://gapminder.org.

RStudio, PBC. 2020. RStudio: Integrated Development Environment for R. RStudio, PBC. http://www.rstudio.com.

Ruppert, David, M. P. Wand, and R. J Carroll. 2003. Semiparametric Regression. Cambridge University Press: Cambridge, UK.

Samet, J. H., M. J. Larson, N. J. Horton, K. Doyle, M. Winter, and R. Saitz. 2003. “Linking Alcohol- and Drug-Dependent Adults to Primary Medical Care: A Randomized Controlled Trial of a Multi-Disciplinary Health Intervention in a Detoxification Unit.” Addiction 98 (4): 509–16. https://doi.org/10.1046/j.1360-0443.2003.00328.x.

Schwarz, A. 2005. The Numbers Game: Baseball’s Lifelong Fascination With Statistics. St. Martin’s Press: New York, NY.

Silge, Julia, and David Robinson. 2016. “Tidytext: Text Mining and Analysis Using Tidy Data Principles in R.” Journal of Open Source Software 1 (3). https://doi.org/10.21105/joss.00037.

Silge, Julia, and David Robinson. 2017. Text Mining with R: A Tidy Approach. O’Reilly Media: Sebastopol, CA. https://www.tidytextmining.com.

Stonebraker, M., D. Abadi, D. J. DeWitt, et al. 2010. “MapReduce and Parallel DBMSs: Friends or Foes?” Communications of the ACM 53 (1): 64–71.

Tan, Pang-Ning, Michael Steinbach, and Vipin Kumar. 2006. Introduction to Data Mining. 1st ed. Pearson Education: New York, NY.

Travers, Jeffrey, and Stanley Milgram. 1969. “An Experimental Study of the Small World Problem.” Sociometry, 425–43.

Tufte, E. R. 1990. Envisioning Information. Graphics Press: Cheshire, CT.

Tufte, E. R. 1997. Visual Explanations: Images and Quantities, Evidence and Narrative. Graphics Press: Cheshire, CT.

Tufte, E. R. 2001. Visual Display of Quantitative Information (Second Edition). Graphics Press: Cheshire, CT.

Tufte, E. R. 2003. The Cognitive Style of PowerPoint. Graphics Press: Cheshire, CT.

Tufte, E. R. 2006. Beautiful Evidence. Graphics Press: Cheshire, CT.

Tukey, J. W. 1990. “Data-Based Graphics: Visual Display in the Decades to Come.” Statistical Science 5 (3): 327–39.

Vinten-Johansen, Peter, Howard Brody, Nigel Paneth, Stephen Rachman, Michael Rip, and David Zuck. 2003. Cholera, Chloroform, and the Science of Medicine: A Life of John Snow. Oxford University Press.

Walker, Kyle. 2020. Tigris: Load Census TIGER/Line Shapefiles into r. https://CRAN.R-project.org/package=tigris.

Wang, Victor. 2006. “The OBP/SLG Ratio: What Does History Say?” By the Numbers 16 (3): 3.

Wang, Yilun, and Michal Kosinski. 2018. “Deep Neural Networks Are More Accurate Than Humans at Detecting Sexual Orientation from Facial Images.” Journal of Personality and Social Psychology 114 (2): 246. https://doi.org/10.1037/pspa0000098.

Wasserstein, Ronald L., and Nicole A. Lazar. 2016. “The ASA’s Statement on p–Values: Context, Process, and Purpose.” The American Statistician 70 (2): 129–33.

Wasserstein, Ronald L., Allen L. Schirm, and Nicole A. Lazar. 2019. “Moving to a World Beyond p < 0.05.” The American Statistician 73 (sup1): 1–19.

Watts, Duncan J, and Steven H Strogatz. 1998. “Collective Dynamics of ‘Small-World’ Networks.” Nature 393 (6684): 440–42.

Wickham, H. 2011. “ASA 2009 Data Expo.” Journal of Computational and Graphical Statistics 20 (2): 281–83.

Wickham, H. 2014. “Tidy Data.” The Journal of Statistical Software 59 (10).

Wickham, H. 2019. Advanced r (Second Edition). CRC Press: Boca Raton, FL.

Wickham, Hadley. 2015. R Packages: Organize, Test, Document, and Share your Code. O’Reilly Media: Sebastopol, CA. http://r-pkgs.had.co.nz/.

Wickham, Hadley. 2016. Ggplot2: Elegant Graphics for Data Analysis. Springer Verlag: New York, NY. https://ggplot2.tidyverse.org.

Wickham, Hadley. 2019. Babynames: US Baby Names 1880-2014. https://CRAN.R-project.org/package=babynames.

Wickham, Hadley. 2020a. Mastering Shiny. O’Reilly Media: Sebastopol, CA. https://mastering-shiny.org/.

Wickham, Hadley. 2020b. Tidyr: Easily Tidy Data with ‘Spread()‘ and ‘Gather()‘ Functions. https://CRAN.R-project.org/package=tidyr.

Wickham, Hadley. 2023. Tidyverse: Easily Install and Load the Tidyverse. https://tidyverse.tidyverse.org.

Wickham, Hadley, Dianne Cook, and Heike Hofmann. 2015. “Visualizing Statistical Models: Removing the Blindfold.” Statistical Analysis and Data Mining: The ASA Data Science Journal 8 (4): 203–25.

Wickham, H., and R. Francois. 2020. Dplyr: A Grammar of Data Manipulation. https://github.com/hadley/dplyr.

Wikipedia. 2016. Hippocratic Oath. Wikimedia Foundation.

Wilkinson, L., D. Wills, D. Rope, A. Norton, and R. Dubbs. 2005. The Grammar of Graphics (Second Edition). Springer Verlag: New York, NY.

Xie, Y. 2014. Dynamic Documents with R and Knitr. CRC Press: Boca Raton, FL.

Yau, N. 2011. Visualize This: The Flowing Data Guide to Design, Visualization, and Statistics. John Wiley & Sons: Hoboken, NJ.

Yau, N. 2013. Data Points: Visualization That Means Something. John Wiley & Sons: Hoboken, NJ.

Zaslavsky, A. M., and N. J. Horton. 1998. “Balancing Disclosure Risk Against the Loss of Nonpublication.” Journal of Official Statistics 14 (4): 411–19. http://www.jos.nu/Articles/abstract.asp?article=144411.