Bishof, N. (2008). Psychologie – Ein Grundkurs für Anspruchsvolle. Kohlhammer, Stuttgart.

Bishop, C. (2006). Pattern Recognition and Machine Learning. Springer.

Cumming, G. (2013). Understanding the new statistics: Effect sizes, confidence intervals, and meta-analysis. Routledge.

Cumming, G. (2014). The new statistics why and how. Psychological science

Fidler, F., & Cumming, G. (2014). Yes, but Don’t Underestimate Estimation Reply to Morey, Rouder, Verhagen, and Wagenmakers (2014). Psychological science, 25(6), 1291-1292.

Dambacher, M., Rolfs, M., and Cavanagh, P. (2011). Visual adaptation of causality. Journal of Vision, 11, article 1061.

Dennett, D.(1998). Brainchildren. MIT Press. Cambridge, MA.

Gelman, A., Carlin, J. B., Stern, H. S., Dunson, D. B., Vehtari, A., & Rubin, D. B. (2013). Bayesian data analysis. CRC press.

Gelman, A., & Stern, H. (2006). The difference between “significant” and “not significant” is not itself statistically significant. The American Statistician, 60(4), 328-331.

Gelman, A., & Hill, J. (2007). Data analysis using regression and multilevel/hierarchical models. Cambridge University Press.

Gelman, A., Hill, J., & Yajima, M. (2012). Why we (usually) don’t have to worry about multiple comparisons. Journal of Research on Educational Effectiveness, 5(2), 189-211.

Gelman, A., & Shalizi, C. R. (2013). Philosophy and the practice of Bayesian statistics. British Journal of Mathematical and Statistical Psychology, 66(1), 8-38.

Gigerenzer, G. (2004). Mindless statistics. The Journal of Socio-Economics, 33(5), 587-606.

Graham, R. L., Knuth, D. E., & Patashnik, O. (1989). Concrete Mathematics. Massachusetts: Addison-Wesley.

Ibrahim, J. G., Chen, M. H., & Sinha, D. (2005). Bayesian survival analysis. John Wiley & Sons, Ltd.

Jaynes, E. T. (2003). Probability theory: the logic of science. Cambridge university press.

Jones, M., & Love, B. C. (2011). Bayesian fundamentalism or enlightenment? On the explanatory status and theoretical contributions of Bayesian models of cognition. Behavioral and Brain Sciences, 34(04), 169-188.

Kline, R. B. (2004). Beyond significance testing: Reforming data analysis methods in behavioral research.

Kruschke, J. (2010). Doing Bayesian data analysis: a tutorial introduction with R. Academic Press.

Miller, J. (2009). What is the probability of replicating a statistically significant effect?. Psychonomic Bulletin & Review, 16(4), 617-640.

Montgomery, D. C., Jennings, C. L., & Kulahci, M. (2011). Introduction to time series analysis and forecasting (Vol. 526). John Wiley & Sons.

Morey, R. D., Rouder, J. N., Verhagen, J., Wagenmakers, E. J., & Morey, R. D. Why hypothesis tests are essential for psychological science: A comment on Cumming. Psychological Science.

Oaksford, M., & Chater, N. (1998). Rationality in an uncertain world: Essays on the cognitive science of human reasoning. Psychology Press/Erlbaum (UK) Taylor & Francis.

Pearl, J. (2000). Causality: models, reasoning and inference. Cambridge: MIT press.

Pratt, J. W. (1962). On the foundations of statistical inference: Discussion. Journal of the American Statistical Association, 57, 314-315.

Rotello, C. M., Heit, E., & Dube, C. (2015). When more data steer us wrong: replications with the wrong dependent measure perpetuate erroneous conclusions. Psychonomic bulletin & review, 22(4), 944-954.

Skinner, B.F. (1959) A case history in scientific method. The American Psychologist. 221-233.

Stone, M. (1976). Strong inconsistency from uniform priors. Journal of the American Statistical Association, 71(353), 114-116.

Trueblood, J. S., Brown, S. D., & Heathcote, A. (2014). The multiattribute linear ballistic accumulator model of context effects in multialternative choice. Psychological review, 121(2), 179.

Tukey, J. W. (1969). Analyzing data: Sanctification or detective work?. American Psychologist, 24(2), 83.