Literaturverzeichnis

Badenes-Ribera, L., Frias-Navarro, D., Iotti, B., Bonilla-Campos, A., & Longobardi, C. (2016). Misconceptions of the p-value among Chilean and Italian Academic Psychologists. Frontiers in Psychology, 7. https://www.frontiersin.org/article/10.3389/fpsyg.2016.01247

Bourier, G. (2011). Wahrscheinlichkeitsrechnung und schließende Statistik: praxisorientierte Einführung mit Aufgaben und Lösungen (7., aktualisierte Aufl). Gabler.

Bourier, G. (2022). Statistik-übungen: Beschreibende statistik – wahrscheinlichkeitsrechnung – schließende statistik (7. Auflage). Springer Gabler.

Briggs, W. M. (2016). Uncertainty: The Soul of Modeling, Probability & Statistics. Springer.

Cohen, J. (1992). A power primer. Psychological Bulletin, 112(1), 155–159.

Forum, W. E. (2020). The Future of Jobs Report 2020. World Economic Forum. https://www3.weforum.org/docs/WEF_Future_of_Jobs_2020.pdf

Gelman, A., Hill, J., & Vehtari, A. (2021). Regression and other stories. Cambridge University Press.

Goodrich, B., Gabry, J., Ali, I., & Brilleman, S. (2020). Rstanarm: Bayesian applied regression modeling via Stan. https://mc-stan.org/rstanarm

Henze, N. (2019). Stochastik: Eine Einführung mit Grundzügen der Maßtheorie: Inkl. zahlreicher Erklärvideos. Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-662-59563-3

Hoekstra, R., Morey, R. D., Rouder, J. N., & Wagenmakers, E.-J. (2014). Robust misinterpretation of confidence intervals. Psychonomic Bulletin & Review, 21(5), 1157–1164. http://www.ejwagenmakers.com/inpress/HoekstraEtAlPBR.pdf

Jaynes, E. T., & Bretthorst, G. L. (2003). Probability theory: The logic of science. Cambridge University Press.

Kabadayi, F. (2024). Smartphone addiction, depression, distress, eustress, loneliness, and sleep deprivation in adolescents: A latent profile and network analysis approach. BMC Psychology, 12(1), 608. https://doi.org/10.1186/s40359-024-02117-6

Kruschke, J. K. (2018). Rejecting or Accepting Parameter Values in Bayesian Estimation. Advances in Methods and Practices in Psychological Science, 1(2), 270–280. https://doi.org/10.1177/2515245918771304

Kurz, S. (2021). Statistical Rethinking with Brms, Ggplot2, and the Tidyverse: Second Edition. https://bookdown.org/content/4857/

Makowski, D., Ben-Shachar, M. S., Chen, S. H. A., & Lüdecke, D. (2019). Indices of Effect Existence and Significance in the Bayesian Framework. Frontiers in Psychology, 10. https://www.frontiersin.org/article/10.3389/fpsyg.2019.02767

McElreath, R. (2020). Statistical rethinking: A Bayesian course with examples in R and Stan (2nd ed.). Taylor and Francis, CRC Press.

Mittag, H.-J., & Schüller, K. (2020). Statistik: Eine Einführung mit interaktiven Elementen. Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-662-61912-4

Morey, R. D., & Rouder, J. N. (2011). Bayes factor approaches for testing interval null hypotheses. Psychological Methods, 16(4), 406–419. https://doi.org/10.1037/a0024377

Pearl, J., Glymour, M., & Jewell, N. P. (2016). Causal inference in statistics: A primer. Wiley.

Poldrack, R. (2022). Statistical Thinking for the 21st Century. https://statsthinking21.github.io/statsthinking21-core-site/index.html

Popper, K. (2013). Logik der Forschung (H. Keuth, Ed.). Akademie Verlag. https://doi.org/10.1524/9783050063782

Sauer, S. (2025). Statistik1. Independently published via Amazon. https://www.amazon.de/Statistik1-Einf%C3%BChrung-Statistik-Schwerpunkt-Prognose-Modellierung/dp/B0F673WGG5

Shmueli, G. (2010). To Explain or to Predict? Statistical Science, 25(3), 289–310. https://doi.org/10.1214/10-STS330

van Kampen, D. (2014). The SSQ model of schizophrenic prodromal unfolding revised: An analysis of its causal chains based on the language of directed graphs. European Psychiatry, 29(7), 437–448. https://doi.org/10.1016/j.eurpsy.2013.11.001

Wasserstein, R. L., & Lazar, N. A. (2016). The ASA’s Statement on p-Values: Context, Process, and Purpose. The American Statistician, 70(2), 129–133. https://doi.org/10.1080/00031305.2016.1154108