Zeitschrift für Politikwissenschaft

, Volume 27, Issue 2, pp 205–220 | Cite as

Warum erfolgreiche Prognosen einfach und unsicher sind

Von der Wahl des richtigen Werkzeugs für Wähler und die Wahlforschung
Forum

Literatur

  1. Allensbach. 2015. Zwischen Sicherheitsbedürfnis und Risikobereitschaft (Bericht). Radolfzell: Allensbach Institut.Google Scholar
  2. Bauer, Thomas, Gerd Gigerenzer, und Walter Krämer. 2014. Warum dick nicht doof macht und Genmais nicht tötet: Über Risiken und Nebenwirkungen der Unstatistik. Frankfurt a.M.: Campus.Google Scholar
  3. Brenke, Karl, und Alexander S. Kritikos. 2017. Wählerstruktur im Wandel. DIW Wochenbericht 84(29):595–606.Google Scholar
  4. Gaissmaier, Wolfgang, und Gerd Gigerenzer. 2012. 9/11, Act II: A fine-grained analysis of regional variations in traffic fatalities in the aftermath of the terrorist attacks. Psychological Science 23(12):1449–1454.CrossRefGoogle Scholar
  5. Gaissmaier, Wolfgang, und Julian N. Marewski. 2011. Forecasting elections with mere recognition from small, lousy samples: A comparison of collective recognition, wisdom of crowds, and representative polls. Judgment and Decision Making 6(1):73–88.Google Scholar
  6. Gaissmaier, Wolfgang, und Hansjörg Neth. 2016. Die Intelligenz einfacher Entscheidungsregeln in einer ungewissen Welt. Controller Magazin 41(2):19–26.Google Scholar
  7. Geman, Stuart, Elie Bienenstock, und René Doursat. 1992. Neural networks and the bias/variance dilemma. Neural Computation 4(1):1–58.CrossRefGoogle Scholar
  8. Gigerenzer, Gerd. 2013. Risiko: Wie man die richtigen Entscheidungen trifft. München: Bertelsmann.Google Scholar
  9. Gigerenzer, Gerd, und Wolfgang Gaissmaier. 2011. Heuristic decision making. Annual Review of Psychology 62(1):451–482.CrossRefGoogle Scholar
  10. Gigerenzer, Gerd, Wolfgang Gaissmaier, Elke Kurz-Milcke, Lisa Schwartz, und Steven Woloshin. 2007. Helping doctors and patients make sense of health statistics. Psychological Science in the Public Interest 8(2):53–96.CrossRefGoogle Scholar
  11. Gigerenzer, Gerd, Ralph Hertwig, und Thorsten Pachur (Hrsg.). 2011. Heuristics: The foundations of adaptive behavior. New York: Oxford University Press.Google Scholar
  12. Gigerenzer, Gerd, und Laura Martignon. 2015. Risikokompetenz in der Schule lernen. In Lernen und Lernstörungen. Bern: Hogrefe.Google Scholar
  13. Gigerenzer, Gerd, Jutta Mata, und Ronald Frank. 2009. Public knowledge of benefits of breast and prostate cancer screening in Europe. Journal of the National Cancer Institute 101(17):1216–1220.CrossRefGoogle Scholar
  14. Gigerenzer, Gerd, Zeno Swijtink, Lorraine J. Daston, Theodore Porter, Lorenz Kruger, und John Beatty. 1990. The empire of chance: how probability changed science and everyday life. Cambridge: Cambridge University Press.Google Scholar
  15. Gigerenzer, Gerd, Peter M. Todd, und ABC Research Group. 1999. Simple heuristics that make us smart. New York: Oxford University Press.Google Scholar
  16. Goldstein, Daniel G., und Gerd Gigerenzer. 2009. Fast and frugal forecasting. International Journal of Forecasting 25(4):760–772.CrossRefGoogle Scholar
  17. Gøtzsche, Peter C., und Karsten J. Jørgensen. 2013. Screening for breast cancer with mammography. The Cochrane Library 2013:CD1877.Google Scholar
  18. Graefe, Andreas, und J. Scott Armstrong. 2012. Predicting elections from the most important issue: a test of the take-the-best heuristic. Journal of Behavioral Decision Making 25(1):41–48.CrossRefGoogle Scholar
  19. Groves, Robert M., Floyd J. Fowler Jr, Mick P. Couper, James M. Lepkowski, Eleanor Singer, und Roger Tourangeau. 2011. Survey methodology. Bd. 561. New York: Wiley.Google Scholar
  20. Hacking, Ian. 1990. The taming of chance. Cambridge: Cambridge University Press.CrossRefGoogle Scholar
  21. Ipsos. 2017. Die Sorgen der Deutschen im Wahljahr 2017 (Bericht). Hamburg: Ipsos Public Affairs.Google Scholar
  22. Jones, Robert P., und Daniel Cox. 2012. Race, class, and culture survey 2012 (Bericht und Daten). University Park, PA: Association of Religion Data Archives (ARDA).Google Scholar
  23. Jung, Matthias. 2017. Stopp dem Demoskopenbashing! Warum Umfrageergebnisse doch nicht so schlecht sind. Die Politische Meinung 543:40–45.Google Scholar
  24. Kahneman, Daniel. 2012. Schnelles Denken, langsames Denken. München: Siedler.Google Scholar
  25. Knight, Frank H. 1921. Risk, uncertainty and profit. Chicago: University of Chicago Press.Google Scholar
  26. Lichtman, Allan J. 2008. The keys to the White House: An index forecast for 2008. International Journal of Forecasting 24(2):301–309.CrossRefGoogle Scholar
  27. Marewski, Julian N., Wolfgang Gaissmaier, Lael J. Schooler, Daniel G. Goldstein, und Gerd Gigerenzer. 2009. Do voters use episodic knowledge to rely on recognition? In Proceedings of the 31st Annual Meeting of the Cognitive Science Society, Hrsg. Niels Taatgen, und Heddrik van Rijn, 2232–2237. Austin: Cognitive Science Society.Google Scholar
  28. Marewski, Julian N., Rüdiger F. Pohl, und Oliver Vitouch. 2010. Recognition-based judgments and decisions: Introduction to the special issue (Vol. 1). Judgment and Decision Making 5(4):207–215.Google Scholar
  29. Marewski, Julian N., Rüdiger F. Pohl, und Oliver Vitouch. 2011. Recognition-based judgments and decisions: Introduction to the special issue (Vol. 2). Judgment and Decision Making 6(1):1–6.Google Scholar
  30. Martignon, Laura, Konstantinos V. Katsikopoulos, und Jan K. Woike. 2008. Categorization with limited resources: A family of simple heuristics. Journal of Mathematical Psychology 52(6):352–361.CrossRefGoogle Scholar
  31. Maslow, Abraham H. 1966. The psychology of science. New York: Harper & Row.Google Scholar
  32. McKenzie, Craig R.M. 2003. Rational models as theories – not standards-of behavior. Trends in Cognitive Sciences 7(9):403–406.CrossRefGoogle Scholar
  33. Moussaïd, Mehdi, Henry Brighton, und Wolfgang Gaissmaier. 2015. The amplification of risk in experimental diffusion chains. Proceedings of the National Academy of Sciences 112(18):5631–5636.CrossRefGoogle Scholar
  34. Moussaïd, Mehdi, Juliane E. Kämmer, Pantelis P. Analytis, und Hansjörg Neth. 2013. Social influence and the collective dynamics of opinion formation. PloS One 8(11):e78433.CrossRefGoogle Scholar
  35. Neth, Hansjörg. 2014. Warum Controller auf Heuristiken setzen sollten. Controlling & Management Review 58(3):22–28.CrossRefGoogle Scholar
  36. Neth, Hansjörg, und Gerd Gigerenzer. 2015. Heuristics: Tools for an uncertain world. In Emerging trends in the social and behavioral sciences, Hrsg. R. Scott, und S. Kosslyn. New York: Wiley.Google Scholar
  37. Neth, Hansjörg, Björn Meder, Amit Kothiyal, und Gerd Gigerenzer. 2014. Homo heuristicus in the financial world: From risk management to managing uncertainty. Journal of Risk Management in Financial Institutions 7(2):134–144.Google Scholar
  38. Neth, Hansjörg, Chris R. Sims, und Wayne D. Gray. 2016. Rational task analysis: A methodology to benchmark bounded rationality. Minds and Machines 26(1–2):125–148.CrossRefGoogle Scholar
  39. Phillips, Nathaniel D., Hansjörg Neth, Jan K. Woike, und Wolfgang Gaissmaier. 2017. FFTrees: A toolbox to create, visualize, and evaluate fast-and-frugal decision trees. Judgment and Decision Making 12(4):344–368.Google Scholar
  40. Rees, Nigel. 2006. Brewer’s famous quotations: 5000 quotations and the stories behind them. London: Cassell.Google Scholar
  41. Russell, Bertrand. 1950. Unpopular essays. (Chapter 2: Philosophy for Laymen). London: Routledge.Google Scholar
  42. Savage, Leonard J. 1954. The foundations of statistics. New York, NY: Dover Publications.Google Scholar
  43. Schröder, Fritz H., Jonas Hugosson, et al, 2014. Screening and prostate cancer mortality: Results of the European randomised study of screening for prostate cancer (ERSPC) at 13 years of follow-up. The Lancet 384(9959):2027–2035.CrossRefGoogle Scholar
  44. Shanteau, James. 1992. How much information does an expert use? Is it relevant? Acta Psychologica 81(1):75–86.CrossRefGoogle Scholar
  45. Sherbino, Jonathan, Kelly Dore, Timothy Wood, Meredith Young, Wolfgang Gaissmaier, Sharyn Krueger, und Geoffrey Norman. 2012. The relation between processing speed and diagnostic errors. Academic Medicine 87(6):785–791.CrossRefGoogle Scholar
  46. Silver, Nate. 2017. The real story of 2016. http://fivethirtyeight.com/features/the-real-story-of-2016. Zugegriffen: 31. Juli 2017.Google Scholar
  47. Soyer, Emre, und Robin M. Hogarth. 2012. The illusion of predictability: How regression statistics mislead experts. International Journal of Forecasting 28(3):695–711.CrossRefGoogle Scholar
  48. Stevenson, Peter W. (2016). Professor who predicted 30 years of presidential elections correctly called a Trump win in September. The Washington Post (11. Sept. 2016).Google Scholar
  49. Surowiecki, James. 2004. The wisdom of crowds. New York: Doubleday.Google Scholar
  50. Todd, Peter M., Gerd Gigerenzer, und ABC Research Group. 2012. Ecological rationality: Intelligence in the world. New York: Oxford University Press.CrossRefGoogle Scholar
  51. Tversky, Amos, und Daniel Kahneman. 1974. Judgment under uncertainty: Heuristics and biases. Science 185(4157):1124–1131.CrossRefGoogle Scholar
  52. Voltaire, alias François-Marie Arouet. 1919. Letter to Frederick William, Prince of Prussia (28.11. 1770). In Voltaire in his letters, Hrsg. S.G. Tallentyre. New York: Putnam’s Sons.Google Scholar
  53. Wegwarth, Odette, Lisa M. Schwartz, Steven Woloshin, Wolfgang Gaissmaier, und Gerd Gigerenzer. 2012. Do physicians understand cancer screening statistics? Annals of Internal Medicine 156(5):340–349.CrossRefGoogle Scholar

Copyright information

© Springer Fachmedien Wiesbaden GmbH 2017

Authors and Affiliations

  1. 1.Sozialpsychologie und Entscheidungsforschung, Fachbereich PsychologieUniversität KonstanzKonstanzDeutschland

Personalised recommendations