Computer‐based teaching and evaluation of introductory statistics for health science students: Some lessons learned

In recent years, it has become possible to introduce health science students to statistical packages at an increasingly early stage in their undergraduate studies. This has enabled teaching to take place in a computer laboratory, using real data, and encouraging an exploratory and research‐oriented approach. This paper briefly describes a hypertext Computer Based Tutorial (CBT) concerned with descriptive statistics and introductory data analysis. The CBT has three primary objectives: the introduction of concepts, the facilitation of revision, and the acquisition of skills for project work. Objective testing is incorporated and used for both self‐assessment and formal examination. Evaluation was carried out with a large group of Health Science students, heterogeneous with regard to their IT skills and basic numeracy. The results of the evaluation contain valuable lessons

Who’s on first

“X-Firsters” hold that there is some normative feature that is fundamental to all others (and, often, that there’s some normative feature that is the “mark of the normative”: all other normative properties have it, and are normative in virtue of having it). This view is taken as a starting point in the debate about which X is “on first.” Little has been said about whether or why we should be X-Firsters, or what we should think about normativity if we aren’t X-Firsters. Hence the chapter’s two main goals. First, to provide a simple argument that one shouldn’t be an X-Firster about the normative domain, which starts with the observation that analogous views have dubious merits in analogous domains. Second, to offer an alternative view—taking normativity to be a determinable explained in terms of its determinates—that offers an interesting way to think about the structure and unity of normativity

A language for the construction of preferences under uncertainty

This paper studies a target-based procedure to rank lotteries that is normatively and observationally equivalent to the expected utility model. In view of this equivalence, the traditional utility-based language for decision making may be substituted with an alternative target-based language. Switching language may have significant modelling consequences. To exemplify, we contrast the utility-based viewpoint of prospect theory against the target-based viewpoint and provide an explanation of Allais’ paradox based on context dependence instead of distorted probabilities.expected utility, prospect theory, target-based decisions, choice anomalies, benchmarking