References

Aschwanden, Christie. 2015. “Science Isn’t Broken: It’s Just a Hell of a Lot Harder Than We Give It Credit For.” FiveThirtyEight. https://fivethirtyeight.com/features/science-isnt-broken/.

———. 2016. “Statisticians Found One Thing They Can Agree on: It’s Time to Stop Misusing p-Values.” FiveThirtyEight. https://fivethirtyeight.com/features/statisticians-found-one-thing-they-can-agree-on-its-time-to-stop-misusing-p-values/.

Blackwell, Matthew. 2023. “A User’s Guide to Statistical Inference and Regression.” https://mattblackwell.github.io/gov2002-book/.

Çetinkaya-Rundel, Mine, and Johanna Hardin. 2021. Introduction to Modern Statistics. OpenIntro. https://openintro-ims.netlify.app/.

Fisher, Ronald A. 1956. “Statistical Methods and Scientific Inference.”

Gelman, Andrew. 2016. “The Problems with p-Values Are Not Just with p-Values.” The American Statistician 70. http://www.tandfonline.com/doi/full/10.1080/00031305.2016.1154108.

Gelman, Andrew, Jennifer Hill, and Aki Vehtari Vehtari. 2020. Regression and Other Stories. Cambridge University Press.

Gelman, Andrew, and Eric Loken. 2021. “The Statistical Crisis in Science.” American Scientist 102 (6): 460. https://doi.org/10.1511/2014.111.460.

Gelman, Andrew, and Hal Stern. 2006. “The Difference Between "Significant" and "Not Significant" Is Not Itself Statistically Significant.” The American Statistician 60 (4): 328–31.

Greenland, Sander, Stephen J. Senn, Kenneth J. Rothman, John B. Carlin, Charles Poole, Steven N. Goodman, and Douglas G. Altman. 2016. “Statistical Tests, p-Values, Confidence Intervals, and Power: A Guide to Misinterpretations.” European Journal of Epidemiology 31: 337–50.

James, Gareth, Daniela Witten, Trevor Hastie, and Robert Tibshirani. 2013. An Introduction to Statistical Learning. Springer. https://www.statlearning.com/.

James, Gareth, Daniela Witten, Trevor Hastie, Robert Tibshirani, and Jonathan Taylor. 2023. An Introduction to Statistical Learning. Springer. https://www.statlearning.com/.

Jordan, Jeremy. 2017. “Hyperparameter Tuning for Machine Learning Models.” https://www.jeremyjordan.me/hyperparameter-tuning/.

Kuhn, Max, and Julia Silge. 2023. Tidy Modeling with r. https://www.tmwr.org/.

Lakens, Daniel. 2022. Improving Your Statistical Inferences. https://doi.org/10.5281/zenodo.6409077.

Lindeløv, Jonas Kristoffer. 2019. “Common Statistical Tests Are Linear Models.” https://lindeloev.github.io/tests-as-linear/.

McElreath, Richard. 2023. “None of the Above.” https://elevanth.org/blog/2023/07/17/none-of-the-above/.

Poole, Charles. 2022. “The Statistical Arc of Epidemiology.” Presented at the "What is the Value of the P-Value?" Panel Discussion, Cosponsored by UNC TraCS, Duke University, and Wake Forest University CTSA Biostatistics, Epidemiology and Research Design (BERD) Cores.

Popper, Karl. 1935. The Logic of Scientific Discovery. Routledge.

Prytherch, Ben. 2022. DSCI 335: Inferential Reasoning in Data Analysis. https://bookdown.org/csu_statistics/dsci_335_spring_2022/.

Sinikumpu, Suvi-Päivikki, Jari Jokelainen, Juha Auvinena, Markku Timonen, and Laura Huilaja. 2021. “Association Between Psychosocial Distress, Sexual Disorders, Self-Esteem and Quality of Life with Male Androgenetic Alopecia: A Population-Based Study with Men at Age 46.” BMJ Open 11 (12).

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.

Zablotski, Yury. 2019. “Statistical Tests Vs. Linear Regression.” https://yury-zablotski.netlify.app/post/statistical-tests-vs-linear-regression/.