• The approach presented here is based on the following general notions about forecasting. First, that most predictions and forecasts contain an irreducible intuitive component. Second, that the intuitive predictions of knowledgeable individuals contain much useful information. Third, that these intuitive judgments are often biased in a predictable manner. Hence, the problem is not whether to accept intuitive predictions at face value or to reject them, but rather how they can be debiased and improved.

  • In this chapter, we discuss the possibility of improving people's inferences in everyday life.

  • This chapter explores some psychological elements of the risk-assessment process. Its basic premises are that both the public and the experts are necessary participants in that process, that assessment is inherently subjective, and that understanding judgmental limitations is crucial to effective decision making.

  • "The study of intuitions and errors in judgment under uncertainty is complicated by several factors: discrepancies between acceptance and application of normative rules; effects of content on the application of rules; Socratic hints that create intuitions whole testing them; demand characteristics of within-subject experiments; subjects' interpretations of experimental messages according to standard conversational rules. The positive analysis of a judgmental error in terms of heuristics may be supplemented by a negative analysis, which seeks to explain why the correct rule is not intuitively compelling. A negative analysis of non-regressive prediction is outlined."

  • In this chapter we sketch some extensions of the range of observations that are normally considered in psychological analyses of judgments under uncertainty. Two levels of responses to uncertainty are discussed.

  • In this chapter we begin by describing the special problem of probability in the curriculum and positing what we want students to end up knowing about probability at the end of their school experience. Next we present some important general issues of what curriculum is and where it comes from, and focus on some concerns about how it relates to students. We then consider alternative forms of the probability curriculum, using current projects as examples of each form. Finally, we summarize the theoretical issues as questions to be asked about any curriculum, and recommend ways to use current curriculum efforts to extend our knowledge of how students think about and learn probability.

  • Although probability theory is now considered by mathematicians as belonging entirely to mathematics and although most subjects use it, its teaching in France is discredited in the eyes of most mathematics teachers. It is dealt with separately, if time is left or if it is required for an examination, and it is the first topic to be omitted in any syllabus reduction. The purpose of this report is an attempt to analyse the causes of this phenomenon and to make some propositions to remedy it, taking into account the work of the INRP group which was in operation from 1973 to 1978.

  • This report on teaching statistics will present the Statistics Focus Group's recommendations under three headings, corresponding to statistics, mathematics, and teaching. A fourth section illustrates ways these recommendations can be put into practice, and a final section offers two meta-recommendations about implementation.

  • The task of this essay is not to urge attention to data and chance in the school curriculum- they are already attracting attention- but to develop this strand of mathematical ideas in a way that makes clear the overall themes and strategies within which individual topics find their natural place.

  • The author seeks to bridge the longstanding gap between behavioral and cognitive perspectives on choice. Acknowledging the existence and the relevance of internal judgments and decisions in the external choices we make, he shows not only how these cognitive processes can be understood in behavioral terms but also how cognitive and behavioral views can be reconciled.