Literatur

Schlüsselwörter

Statistik, Prognose, Modellierung, R, Datenanalyse, Regression

Ainali. (2007). Standard deviation diagram micro [Artwork]. https://commons.wikimedia.org/w/index.php?curid=3141713
Anscombe, F. J. (1973). Graphs in statistical analysis. The American Statistician, 27(1), 17–21.
Arad, C. (2024, June 5). Kylian Mbappe: Gehalt und Vermögen im Überblick (2024). ftd.de. https://www.ftd.de/vermoegen/mbappe-gehalt-vermoegen/
Barrett, M. (2021). Ggokabeito: ’Okabe-ItoScales for ’Ggplot2’ and ’ggraph’ [Manual]. https://CRAN.R-project.org/package=ggokabeito
Berger, G. (2019, December 10). The Jobs of Tomorrow: LinkedIn’s 2020 Emerging Jobs Report. https://www.linkedin.com/blog/member/career/the-jobs-of-tomorrow-linkedins-2020-emerging-jobs-report
Bortz, J., & Schuster, C. (2010). Statistik für Human- und Sozialwissenschaftler. Springer. https://doi.org/10.1007/978-3-642-12770-0
Bowne-Anderson, H. (2018). What Data Scientists Really Do, According to 35 Data Scientists. Harvard Business Review. https://hbr.org/2018/08/what-data-scientists-really-do-according-to-35-data-scientists
Broman, K. W., & Woo, K. H. (2018). Data Organization in Spreadsheets. The American Statistician, 72(1), 2–10. https://doi.org/10.1080/00031305.2017.1375989
Bundesamt, S. (2023-003-272023-003-27). Körpermaße nach Altersgruppen und Geschlecht. Statistisches Bundesamt. https://www.destatis.de/DE/Themen/Gesellschaft-Umwelt/Gesundheit/Gesundheitszustand-Relevantes-Verhalten/Tabellen/liste-koerpermasse.html
Bundesbank, D. (2023). Household wealth and finances in Germany: Results of the 2021 household wealth survey. Deutsche Bundesbank. https://www.bundesbank.de/resource/blob/908924/3ef9d9a4eaeae8a8779ccec3ac464970/mL/2023-04-vermoegensbefragung-data.pdf
Çetinkaya-Runde, M., & Hardin, J. (2021). Introduction to Modern Statistics. https://openintro-ims.netlify.app/
Çetinkaya-Rundel, M., Diez, D., Bray, A., Kim, A. Y., Baumer, B., Ismay, C., Paterno, N., & Barr, C. (2024). Openintro: Datasets and supplemental functions from ’OpenIntro’ textbooks and labs. https://CRAN.R-project.org/package=openintro
Cmglee. (2015). English: Geometric visualisation of the variance of the example distribution (2, 4, 4, 4, 5, 5, 7, 9) on w:Standard deviation. [artwork]. https://commons.wikimedia.org/w/index.php?curid=39472834
Cohen, J. (1992). A power primer. Psychological Bulletin, 112(1), 155–159.
Cohen, J., Cohen, P., West, S. G., & Aiken, L. S. (2003). Applied multiple regression/correlation analysis for the behavioral sciences, 3rd ed. Lawrence Erlbaum.
Cui, B. (2024). DataExplorer: Automate data exploration and treatment. https://CRAN.R-project.org/package=DataExplorer
DenisBoigelot. (2011). English: Redesign File:Correlation_examples.png using vector graphics (SVG file) [Artwork]. https://commons.wikimedia.org/w/index.php?curid=15165296
Deutscher Wetterdienst. (2025a). Regional averages DE, monthly air temperature mean. https://opendata.dwd.de/climate_environment/CDC/regional_averages_DE/monthly/air_temperature_mean/.
Deutscher Wetterdienst. (2025b). Regional averages DE, monthly precipitation mean. https://opendata.dwd.de/climate_environment/CDC/regional_averages_DE/monthly/precipitation/.
Downey, A. (2023). Probably overthinking it: How to use data to answer questions, avoid statistical traps, and make better decisions. The University of Chicago Press.
Fisher, D., & Meyer, M. (2018). Making data visual: A practical guide to using visualization for insight. O’Reilly.
Fitzmaurice, G. (2017). Same Stats, Different Graphs: Generating Datasets with Varied Appearance and Identical Statistics through Simulated Annealing. Autodesk Research. https://www.research.autodesk.com/publications/same-stats-different-graphs/
flaticon. (2024). Professor [Artwork]. https://www.flaticon.com/de/kostenlose-icons/professor
Gelman, A., Hill, J., & Vehtari, A. (2021). Regression and other stories. Cambridge University Press.
Goren, A., Vaño-Galván, S., Wambier, C. G., McCoy, J., Gomez-Zubiaur, A., Moreno-Arrones, O. M., Shapiro, J., Sinclair, R. D., Gold, M. H., Kovacevic, M., Mesinkovska, N. A., Goldust, M., & Washenik, K. (2020). A preliminary observation: Male pattern hair loss among hospitalized COVID-19 patients in SpainA potential clue to the role of androgens in COVID-19 severity. Journal of Cosmetic Dermatology, 19(7), 1545–1547. https://doi.org/10.1111/jocd.13443
Habitator terrae. (2021). Deutsch: Fünfjährig gemittelte Abweichung der Lufftemperatur in Deutschland vom langjährigem Mittel 1951 bis 1980 [diagramm]. https://commons.wikimedia.org/wiki/File:%C3%84nderung_der_Lufttemperatur_in_Deutschland.gif
Haug, S., Castro, R. P., Kwon, M., Filler, A., Kowatsch, T., & Schaub, M. P. (2015). Smartphone use and smartphone addiction among young people in Switzerland. Journal of Behavioral Addictions, 4(4), 299–307. https://doi.org/10.1556/2006.4.2015.037
Hornik, K., Ligges, U., & Zeileis, A. (2023). Changes on CRAN. The R Journal, 15, 295–296.
Horst, A. (2023). Tidy Data [Artwork]. https://allisonhorst.com/
Horst, A. (2024). Statistics Artwork [Artwork]. https://allisonhorst.com/
Hou, J., Walsh, P. P., & Zhang, J. (2015). The dynamics of Human Development Index. The Social Science Journal, 52(3), 331–347. https://doi.org/10.1016/j.soscij.2014.07.003
Ichihara, Y. G., Okabe, M., Iga, K., Tanaka, Y., Musha, K., & Ito, K. (2008). Color universal design: The selection of four easily distinguishable colors for all color vision types. Color Imaging XIII: Processing, Hardcopy, and Applications, 6807, 206–213. https://doi.org/10.1117/12.765420
imgflip. (2024a). Imageflip Bill Gates Meme [Artwork]. https://imgflip.com
imgflip. (2024b). Imageflip Kermit Meme [Artwork]. https://imgflip.com
imgflip. (2024c). Imageflip Meme [Artwork]. https://imgflip.com
imgflip. (2024d). Imageflip One does not simply [Artwork]. https://imgflip.com
imgflip. (2024e). Imageflip Tom Cruise Meme [Artwork]. https://imgflip.com
imgflip. (2024f). Yoda Jealous Girl Friend Meme [Artwork]. https://imgflip.com
International, T. (2017, January 25). Corruption Perceptions Index 2016. Transparency.org. https://www.transparency.org/en/news/corruption-perceptions-index-2016
Ismay, C., & Kim, A. Y.-S. (2020). Statistical inference via data science: A ModernDive into R and the Tidyverse. CRC Press / Taylor & Francis Group. https://moderndive.com/
Kaplan, D. T. (2009). Statistical modeling: A fresh approach. CreateSpace. https://dtkaplan.github.io/SM2-bookdown/
Kassambara, A. (2023). Ggpubr: ’ggplot2’ based publication ready plots. https://CRAN.R-project.org/package=ggpubr
Kosinski, M., Stillwell, D., & Graepel, T. (2013). Private traits and attributes are predictable from digital records of human behavior. Proceedings of the National Academy of Sciences, 110(15), 5802–5805. https://doi.org/10.1073/pnas.1218772110
Kuhn, M., Vaughan, D., & Hvitfeldt, E. (2024). Yardstick: Tidy characterizations of model performance. https://CRAN.R-project.org/package=yardstick
Kwon, M., Kim, D.-J., Cho, H., & Yang, S. (2013). The smartphone addiction scale: Development and validation of a short version for adolescents. PloS One, 8(12), e83558. https://doi.org/10.1371/journal.pone.0083558
Lalwani, P., Mishra, M. K., Chadha, J. S., & Sethi, P. (2022). Customer churn prediction system: A machine learning approach. Computing, 104(2), 271–294. https://doi.org/10.1007/s00607-021-00908-y
Lieberoth, A., Rasmussen, J., Stoeckli, S., Tran, T., Ćepulić, D.-B., Han, H., Lin, S.-Y., Tuominen, J., Travaglino, G., & Vestergren, S. (2022). COVIDiSTRESS global survey. https://doi.org/10.17605/OSF.IO/Z39US
Lovett, M. C., & Greenhouse, J. B. (2000). Applying Cognitive Theory to Statistics Instruction. The American Statistician, 54(3), 196–206. https://doi.org/10.1080/00031305.2000.10474545
Lüdecke, D., Ben-Shachar, M. S., Patil, I., Wiernik, B. M., Bacher, E., Thériault, R., & Makowski, D. (2022). Easystats: Framework for easy statistical modeling, visualization, and reporting. CRAN. https://doi.org/10.32614/CRAN.package.easystats
Lyon, A. (2014). Why are Normal Distributions Normal? The British Journal for the Philosophy of Science, 65(3), 621–649. https://doi.org/10.1093/bjps/axs046
M7. (2004). Savinelli’s Italian smoking pipe [Artwork]. https://commons.wikimedia.org/wiki/File:Pipa_savinelli.jpg
MacKay, R. J., & Oldford, R. W. (2000). Scientific Method, Statistical Method and the Speed of Light. Statistical Science, 15(3), 254–278. https://doi.org/10.1214/ss/1009212817
Maphry. (2009). Seesaw with mean [Artwork]. https://commons.wikimedia.org/w/index.php?curid=79390659
Marks-Anglin, Arielle and Chen, Yong. (2020). A historical review of publication bias. Research Synthesis Methods, 11(6), 725–742. https://doi.org/10.1002/jrsm.1452
Matthews, R. (2000b). Storks Deliver Babies (p= 0.008). Teaching Statistics, 22(2), 36–38. https://doi.org/10.1111/1467-9639.00013
Matthews, R. (2000a). Storks Deliver Babies (p= 0.008). Teaching Statistics, 22(2), 36–38. https://doi.org/10.1111/1467-9639.00013
Menk. (2014, July 29). Linear regression [computer code]. https://texample.net/tikz/examples/linear-regression/
Messerli, F. H. (2012). Chocolate Consumption, Cognitive Function, and Nobel Laureates. New England Journal of Medicine, 367(16), 1562–1564. https://doi.org/10.1056/NEJMon1211064
Mittag, H.-J., & Schüller, K. (2020). Statistik: Eine Einführung mit interaktiven Elementen. Springer. https://doi.org/10.1007/978-3-662-61912-4
Moore, B. (2015, April 9). Recreating the vaccination heatmaps in R. Benomics. https://benjaminlmoore.wordpress.com/2015/04/09/recreating-the-vaccination-heatmaps-in-r/
Mulukom, V. van, Muzzulini, B., Rutjens, B., Lissa, C. J. van, & Farias, M. (2020). Psychological impact of COVID-19 pandemic. https://doi.org/10.17605/OSF.IO/TSJNB
Obels, P., Lakens, D., Coles, N. A., Gottfried, J., & Green, S. A. (2020). Analysis of Open Data and Computational Reproducibility in Registered Reports in Psychology. Advances in Methods and Practices in Psychological Science, 3(2), 229–237. https://doi.org/10.1177/2515245920918872
Oestreich, M., & Romberg, O. (2014). Keine Panik vor Statistik!: Erfolg und Spaß im Horrorfach nichttechnischer Studiengänge. Springer. https://doi.org/10.1007/978-3-658-04605-7
Okabe, M., & Ito, K. (2023). Color Universal Design (CUD) / Colorblind Barrier Free. https://jfly.uni-koeln.de/color/
Patil, I. (2021). Visualizations with statistical details: The ’ggstatsplot’ approach. Journal of Open Source Software, 6(61), 3167. https://doi.org/10.21105/joss.03167
Pearl, J., & Mackenzie, D. (2018). The book of why: The new science of cause and effect. Basic Books.
Pearson, K. (1896). VII. Mathematical contributions to the theory of evolution.—III. Regression, heredity, and panmixia. Philosophical Transactions of the Royal Society of London. Series A, Containing Papers of a Mathematical or Physical Character, 187, 253–318. https://doi.org/10.1098/rsta.1896.0007
Plesser, H. E. (2018). Reproducibility vs. Replicability: A Brief History of a Confused Terminology. Frontiers in Neuroinformatics, 11, 76. https://doi.org/10.3389/fninf.2017.00076
Poldrack, R. A. (2023). Statistical thinking: Analyzing data in an uncertain world. Princeton University Press. https://statsthinking21.github.io/statsthinking21-core-site/
R Core Team. (2024). R: A language and environment for statistical computing. R Foundation for Statistical Computing. https://www.R-project.org/
Roser, M., Appel, C., & Ritchie, H. (2013). Human Height [Data set]. In Our World in Data. https://ourworldindata.org/human-height
Rothstein, H. R. (2014). Publication Bias. In Wiley StatsRef: Statistics Reference Online. John Wiley. https://doi.org/10.1002/9781118445112.stat07071
Sauer, S. (2017). Dataset ’predictors of performance in stats test’ [Data set]. Open Science Framework. https://doi.org/10.17605/OSF.IO/SJHUY
Sauer, S. (2019). Moderne Datenanalyse mit R: Daten einlesen, aufbereiten, visualisieren und modellieren. Springer. https://www.springer.com/de/book/9783658215866
Scherer, C., Radchuk, V., Staubach, C., Müller, S., Blaum, N., Thulke, H., & Kramer‐Schadt, S. (2019). Seasonal host life‐history processes fuel disease dynamics at different spatial scales. Journal of Animal Ecology, 88(11), 1812–1824. https://doi.org/10.1111/1365-2656.13070
Shimizu, Y. (2022). Multiple Desirable Methods in Outlier Detection of Univariate Data With R Source Codes. Frontiers in Psychology, 12, 819854. https://doi.org/10.3389/fpsyg.2021.819854
Simmons, J. P., Nelson, L. D., & Simonsohn, U. (2011). False-Positive Psychology: Undisclosed Flexibility in Data Collection and Analysis Allows Presenting Anything as Significant. Psychological Science, 22(11), 1359–1366. https://doi.org/10.1177/0956797611417632
Spurzem, L. (2017). VW 1303 von Wiking in 1:87. https://de.wikipedia.org/wiki/Modellautomobil#/media/File:Wiking-Modell_VW_1303_(um_1975).JPG
Stigler, S. M. (2016). The seven pillars of statistical wisdom. Harvard University Press.
Transfermarkt. (2024). Die wertvollsten Fußball-Spieler. https://www.transfermarkt.de/spieler-statistik/wertvollstespieler/marktwertetop/spielerposition_id/8/page/12
van Panhuis, W. G., Grefenstette, J., Jung, S. Y., Chok, N. S., Cross, A., Eng, H., Lee, B. Y., Zadorozhny, V., Brown, S., Cummings, D., & Burke, D. S. (2013). Contagious Diseases in the United States from 1888 to the Present. New England Journal of Medicine, 369(22), 2152–2158. https://doi.org/10.1056/NEJMms1215400
Ward, A. F., Duke, K., Gneezy, A., & Bos, M. W. (2017). Brain Drain: The Mere Presence of One’s Own Smartphone Reduces Available Cognitive Capacity. Journal of the Association for Consumer Research, 2(2), 140–154. https://doi.org/10.1086/691462
Wickham, H. (2016). ggplot2: Elegant graphics for data analysis. Springer-Verlag New York. https://ggplot2.tidyverse.org
Wickham, H. (2023). Tidy-Data-Sinnbild [Artwork]. https://r4ds.hadley.nz/data-tidy#fig-tidy-structure
Wickham, H., Averick, M., Bryan, J., Chang, W., McGowan, L. D., François, R., Grolemund, G., Hayes, A., Henry, L., Hester, J., Kuhn, M., Pedersen, T. L., Miller, E., Bache, S. M., Müller, K., Ooms, J., Robinson, D., Seidel, D. P., Spinu, V., … Yutani, H. (2019). Welcome to the tidyverse. Journal of Open Source Software, 4(43), 1686. https://doi.org/10.21105/joss.01686
Wickham, H., & Grolemund, G. (2018). R für Data Science: Daten importieren, bereinigen, umformen, modellieren und visualisieren (F. Langenau, Trans.). O’Reilly. https://r4ds.had.co.nz/index.html
Wilke, C. (2019). Fundamentals of data visualization: A primer on making informative and compelling figures. O’Reilly. https://clauswilke.com/dataviz/
Wilke, C. (2024). Wilkelab/practicalgg. Wilke Lab. https://github.com/wilkelab/practicalgg
Wilke, S. (2013, June 26). Trends der Lufttemperatur [Bericht]. Umweltbundesamt; Umweltbundesamt. https://www.umweltbundesamt.de/daten/klima/trends-der-lufttemperatur
World Economic Forum. (2020). The Future of Jobs Report 2020. World Economic Forum. https://www3.weforum.org/docs/WEF_Future_of_Jobs_2020.pdf