References

Heinzen et al. (2021)
R Core Team (2022)
Robinson, Hayes, and Couch (2023)
Fox, Weisberg, and Price (2023)
Fox, Weisberg, and Price (2022)
Maindonald and Braun (2022)
Dowle and Srinivasan (2023)
Wickham et al. (2023)
Croissant and Graves (2022)
Kim, Ismay, and Chunn (2021)
Hyndman et al. (2023)
Hyndman (2023)
Bryan (2023)
Pena and Slate (2019)
Xie (2023)
Kim and Ismay (2022)
Çetinkaya-Rundel et al. (2022)
Croissant, Millo, and Tappe (2023)
Cannon et al. (2019)
Wickham (2023)

Bryan, Jennifer. 2023. Gapminder: Data from Gapminder. https://CRAN.R-project.org/package=gapminder.

Cannon, Ann, George Cobb, Bradley Hartlaub, Julie Legler, Robin Lock, Thomas Moore, Allan Rossman, and Jeffrey Witmer. 2019. Stat2Data: Datasets for Stat2. https://github.com/statmanrobin/Stat2Data.

Çetinkaya-Rundel, Mine, David Diez, Andrew Bray, Albert Y. Kim, Ben Baumer, Chester Ismay, Nick Paterno, and Christopher Barr. 2022. Openintro: Data Sets and Supplemental Functions from OpenIntro Textbooks and Labs. https://CRAN.R-project.org/package=openintro.

Croissant, Yves, and Spencer Graves. 2022. Ecdat: Data Sets for Econometrics. https://www.r-project.org.

Croissant, Yves, Giovanni Millo, and Kevin Tappe. 2023. Plm: Linear Models for Panel Data. https://CRAN.R-project.org/package=plm.

Dowle, Matt, and Arun Srinivasan. 2023. Data.table: Extension of ‘Data.frame‘. https://CRAN.R-project.org/package=data.table.

Fox, John, Sanford Weisberg, and Brad Price. 2022. carData: Companion to Applied Regression Data Sets. https://CRAN.R-project.org/package=carData.

———. 2023. Car: Companion to Applied Regression. https://CRAN.R-project.org/package=car.

Heinzen, Ethan, Jason Sinnwell, Elizabeth Atkinson, Tina Gunderson, and Gregory Dougherty. 2021. Arsenal: An Arsenal of r Functions for Large-Scale Statistical Summaries. https://CRAN.R-project.org/package=arsenal.

Hyndman, Rob. 2023. Fpp2: Data for "Forecasting: Principles and Practice" (2nd Edition). https://CRAN.R-project.org/package=fpp2.

Hyndman, Rob, George Athanasopoulos, Christoph Bergmeir, Gabriel Caceres, Leanne Chhay, Kirill Kuroptev, Mitchell O’Hara-Wild, et al. 2023. Forecast: Forecasting Functions for Time Series and Linear Models. https://CRAN.R-project.org/package=forecast.

Kim, Albert Y., and Chester Ismay. 2022. Moderndive: Tidyverse-Friendly Introductory Linear Regression. https://CRAN.R-project.org/package=moderndive.

Kim, Albert Y., Chester Ismay, and Jennifer Chunn. 2021. Fivethirtyeight: Data and Code Behind the Stories and Interactives at FiveThirtyEight. https://github.com/rudeboybert/fivethirtyeight.

Maindonald, John H, and W. John Braun. 2022. DAAG: Data Analysis and Graphics Data and Functions. https://gitlab.com/daagur.

Pena, Edsel A., and Elizabeth H. Slate. 2019. Gvlma: Global Validation of Linear Models Assumptions. https://CRAN.R-project.org/package=gvlma.

R Core Team. 2022. R: A Language and Environment for Statistical Computing. Vienna, Austria: R Foundation for Statistical Computing. https://www.R-project.org/.

Robinson, David, Alex Hayes, and Simon Couch. 2023. Broom: Convert Statistical Objects into Tidy Tibbles. https://CRAN.R-project.org/package=broom.

Wickham, Hadley. 2023. Tidyverse: Easily Install and Load the Tidyverse. https://CRAN.R-project.org/package=tidyverse.

Wickham, Hadley, Romain François, Lionel Henry, Kirill Müller, and Davis Vaughan. 2023. Dplyr: A Grammar of Data Manipulation. https://CRAN.R-project.org/package=dplyr.

Xie, Yihui. 2023. Knitr: A General-Purpose Package for Dynamic Report Generation in r. https://yihui.org/knitr/.