References
- Adams, B., Baller, D., Jonas, B., Joseph, A.-C., and Cummiskey, K. (2021), “Computational Skills for Multivariable Thinking in Introductory Statistics,” Journal of Statistics and Data Science Education, 29, S123–S131.
- Burckhardt, P., Nugent, R., and Genovese, C. R. (2021), “Teaching Statistical Concepts and Modern Data Analysis With a Computing-Integrated Learning Environment,” Journal of Statistics and Data Science Education, 29, S61–S73.
- Carver, R., Everson, M., Gabrosek, J., Horton, N., Lock, R., Mocko, M., et al. (2016), Guidelines for Assessment and Instruction in Statistics Education (GAISE) College Report (Tech. Rep.). Belmont, CA: American Statistical Association.
- Chambers, J. M., Cleveland, W. S., Kleiner, B., and Tukey, P. (1983), Graphical Methods for Data Analysis, Wadsworth.
- Cohen, J. (1988), Statistical Power Analysis for the Behavioral Sciences (2nd ed.), Hillsdale, NJ: Lawrence Erlbaum.
- Cooper, L. L. (2018), “Assessing Students’ Understanding of Variability in Graphical Representations That Share the Common Attribute of Bars,” Journal of Statistics Education, 26, 110–124. DOI: https://doi.org/10.1080/10691898.2018.1473060.
- Doi, J., Potter, G., Wong, J., Alcaraz, I., and Chi, P. (2016), “Web Application Teaching Tools for Statistics Using R and Shiny,” Technology Innovations in Statistics Education, 9, 1–33. DOI: https://doi.org/10.5070/T591027492.
- Donoghue, T., Voytek, B., and Ellis, S. E. (2021), “Teaching Creative and Practical Data Science at Scale,” Journal of Statistics and Data Science Education, 29, S27–S39. Available at: DOI: https://doi.org/10.1080/10691898.2020.1860725.
- Fawcett, L. (2018), “Using Interactive Shiny Applications to Facilitate Research-Informed Learning and Teaching,” Journal of Statistics Education, 26, 2–16. DOI: https://doi.org/10.1080/10691898.2018.1436999.
- Gerbing, D. (2020), R Visualizations: Derive Meaning from Data, Boca Raton, FL: CRC Press.
- Gerbing, D. (2021), “lessR: Less Code, More Results [Computer Software Manual].” Available at: https://cran.r-project.org/package=lessR (R package version 4.0.3)
- Hancock, S. A., and Rummerfield, W. (2020), “Simulation Methods for Teaching Sampling Distributions: Should Hands-on Activities Precede the Computer?” Journal of Statistics Education, 28, 9–17. DOI: https://doi.org/10.1080/10691898.2020.1720551.
- Horton, N. J., and Hardin, J. S. (2021), “Integrating Computing in the Statistics and Data Science Curriculum: Creative Structures, Novel Skills and Habits, and Ways to Teach Computational Thinking,” Journal of Statistics and Data Science Education, 29, S1–S3.
- Kaplan, D., and Pruim, R. (2021), “ggformula: Formula Interface to the Grammar of Graphics [Computer Software Manual].” Available at: https://CRAN.R-project.org/package=ggformula(Rpackageversion0.10.1)
- Kasprowicz, T., and Musumeci, J. (2015), “Teaching Students Not to Dismiss the Outermost Observations in Regressions,” Journal of Statistics Education, 23. DOI: https://doi.org/10.1080/10691898.2015.11889749.
- Kim, B., and Henke, G. (2021), “Easy-to-use Cloud Computing for Teaching Data Science,” Journal of Statistics and Data Science Education, 29, S103–S111. Available at: DOI: https://doi.org/10.1080/10691898.2020.1860726.
- Lane, D. M. (2015), “Simulations of the Sampling Distribution of the Mean do not Necessarily Mislead and can Facilitate Learning,” Journal of Statistics Education, 23. Available at: DOI: https://doi.org/10.1080/10691898.2015.11889738.
- Loy, A., Kuiper, S., and Chihara, L. (2019), “Supporting Data Science in the Statistics Curriculum,” Journal of Statistics Education, 27(1), 2–11. Retrieved from DOI: https://doi.org/10.1080/10691898.2018.1564638.
- Lumley, T. (2020), “Leaps: Regression Subset Selection [Computer Software Manual].” https://CRAN.R-project.org/package=leaps(Rpackageversion3.1)
- Murdoch, D., and Chow, E. D. (2020), “Ellipse: Functions for Drawing Ellipses and Ellipse-Like Confidence Regions [Computer Software Manual],” https://CRAN.R-project.org/package=ellipse(Rpackageversion0.4.2)
- Nolan, D., and Lang, D. T. (2010), “Computing in the Statistics Curricula,” The American Statistician, 64, 97–107. DOI: https://doi.org/10.1198/tast.2010.09132.
- Pruim, R., Kaplan, D. T., and Horton, N. J. (2017), “The Mosaic Package: Helping Students to ’Think With Data’ Using r,” The R Journal, 9, 77–102. DOI: https://doi.org/10.32614/RJ-2017-024.
- R Core Team. (2021), R: A Language and Environment for Statistical Computing [Computer software manual]. Vienna, Austria. Available at: https://www.R-project.org/
- Ross, K., and Sun, D. L. (2019), “Symbulate: Simulation in the Language of Probability,” Journal of Statistics Education, 27, 12–28. DOI: https://doi.org/10.1080/10691898.2019.1600387.
- Rossman, A., and Chance, B. (2021), Rossman/Chance Applet Collection. Available at: https://www.rossmanchance.com/applets/
- RStudio (2021), RStudio Education. Available at: https://education.rstudio.com/learn/beginner/
- Sarkar, D. (2008), Lattice: Multivariate Data Visualization With R, New York: Springer. (ISBN 978-0-387-75968-5)
- Schauberger, P., and Walker, A. (2021), openxlsx: Read, write and edit xlsx files [Computer software manual]. Available at: https://CRAN.R-project.org/package=openxlsx(Rpackageversion4.2.4)
- Sigal, M. J., and Chalmers, R. P. (2016), “Play It Again: Teaching Statistics With Monte Carlo Simulation,” Journal of Statistics Education, 24, 136–156. Available at: DOI: https://doi.org/10.1080/10691898.2016.1246953.
- Pandas Development Team (2021), pandas-dev/pandas: Pandas. Zenodo. Available at: DOI: https://doi.org/10.5281/zenodo.3509134.
- Tukey, J. W. (1977), Exploratory Data Analysis, Addison-Wesley.
- Wickham, H. (2014), “Tidy Data,” Journal of Statistical Software, 59, 1–23. DOI: https://doi.org/10.18637/jss.v059.i10.
- Wickham, H. (2016), ggplot2: Elegant Graphics for Data Analysis, New York: Springer-Verlag.
- Wickham, H. (2021), tidyr: Tidy Messy Data [Computer software manual]. Available at: https://CRAN.R-project.org/package=tidyr(Rpackageversion1.1.4)
- Wickham, H., François, R., Henry, L., and Müller, K. (2021), “dplyr: A Grammar of Data Manipulation [Computer software manual].” https://CRAN.R-project.org/package=dplyr(Rpackageversion1.0.7)
- Xie, Y. (2016), bookdown: Authoring Books and Technical Documents With R Markdown, Boca Raton, FL: Chapman and Hall/CRC. Available at: https://github.com/rstudio/bookdown (ISBN 978-1138700109)