From the content: Intuition and mathematics (didactical points of view, networks related to stochastics, intuitions and mathematics as key for understanding, history of ideas and their mathematization); intuitive ideas in classic statistics (interpretation of probability; random choice; expected value; variance); intuitive ideas in the Bayes approach (ratio of chances and degree of confidence, encouragement and thinking in informations, Bayes formula structures thinking, Bayes formula structures applications); intuitive ideas by persons (research framework; symmetry and basic space; relative frequencies and probability; causal relationships and stochastic dependency; statistical assessment; consequences for empirical research and education).
The CAUSE Research Group is supported in part by a member initiative grant from the American Statistical Association’s Section on Statistics and Data Science Education