Literatur
Anderson, Andrew A. 2019. “Assessing Statistical Results: Magnitude, Precision, and Model Uncertainty.” The American Statistician 73 (sup1): 118–21. https://doi.org/10.1080/00031305.2018.1537889.
Efron, B. 1979. “Bootstrap Methods: Another Look at the Jackknife.” The Annals of Statistics 7 (1): 1–26. https://doi.org/10.1214/aos/1176344552.
Fahrmeir, L., T. Kneib, and S. Lang. 2009. Regression. Springer. http://link.springer.com/book/10.1007/978-3-642-01837-4.
Gardner, M J, and D G Altman. 1986. “Confidence Intervals Rather Than P Values: Estimation Rather Than Hypothesis Testing.” British Medical Journal (Clinical Research Ed.) 292 (6522): 746–50.
Hesterberg, Tim C. 2015. “What Teachers Should Know About the Bootstrap: Resampling in the Undergraduate Statistics Curriculum.” The American Statistician 69 (4): 371–86. https://doi.org/10.1080/00031305.2015.1089789.
Ho, Joses, Tayfun Tumkaya, Sameer Aryal, Hyungwon Choi, and Adam Claridge-Chang. 2019. “Moving Beyond P Values: Data Analysis with Estimation Graphics.” Nature Methods 16 (7): 565–66. https://doi.org/10.1038/s41592-019-0470-3.
Ihaka, Ross, and Robert Gentleman. 1996. “R: A Language for Data Analysis and Graphics.” Journal of Computational and Graphical Statistics 5 (3): 299–314. https://doi.org/10.1080/10618600.1996.10474713.
Ismay, Chester, and Albert Y. Kim. 2021. ModernDive: Statistical Inference via Data Science. https://moderndive.com/.
Knuth, D. E. 1984. “Literate Programming.” The Computer Journal 27 (2): 97–111. https://doi.org/10.1093/comjnl/27.2.97.
Sauer, Sebastian. 2019. Moderne Datenanalyse mit R: Daten einlesen, aufbereiten, visualisieren, modellieren und kommunizieren. FOM-Edition. Wiesbaden: Springer Fachmedien Wiesbaden. https://doi.org/10.1007/978-3-658-21587-3.
Sikkink, P. G., A. F. Zuur, E. N. Ieno, and G. M. Smith. 2007. “Monitoring for Change: Using Generalised Least Squares, Non-Metric Multidimensional Scaling, and the Mantel Test on Western Montana Grasslands.” In Analysing Ecological Data, edited by Alain F. Zuur, Elena N. Ieno, and Graham M. Smith, 463–84. Statistics for Biology and Health. New York, NY: Springer. https://doi.org/10.1007/978-0-387-45972-1_26.
Wasserstein, Ronald L., and Nicole A. Lazar. 2016. “The ASA Statement on p-Values: Context, Process, and Purpose.” The American Statistician 70 (2): 129–33. https://doi.org/10.1080/00031305.2016.1154108.
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. https://doi.org/10.1080/00031305.2019.1583913.
Wickham, Hadley. 2020. Ggplot2: Elegant Graphics for Data Analysis. 3rd, in progress.
Wickham, Hadley, and Garrett Grolemund. 2021. R for Data Science. https://r4ds.had.co.nz/.
Xie, Yihui, J. J. Allaire, and Garrett Grolemund. 2021. R Markdown: The Definitive Guide. https://bookdown.org/yihui/rmarkdown/.
Zuur, A. F., E. Ieno, and E. Meesters. 2009. A Beginner’s Guide to R. Springer.