Literature Index

Data are hot! Everyone -- students, teachers, parents, employers -- is interested in data, but few know how to collect and interpret data intelligently. Data is the basis of science, and statistical thinking is key to the scientific method, yet few graduates of high school and college understand how science works. For these and other reasons, statistics must become a major component of the modern K-12 mathematics curriculum and achieve a stronger presence in the undergraduate curriculum, as recommended by a wide variety of educational groups.

This is a discussion of a single-day workshop which provides statistics in-service training to a large number of the high school mathematics teachers in the state of Wisconsin.

Performance on problems included in the fourth administration of NAEP suggest that roughly half of secondary students believe in the independence of random events. In the study reported here about half of the subjects who appeared to be reasoning normatively on a question concerning the most likely outcome of five flips of a fair coin gave a logically inconsistent answer on a follow-up question about the least likely outcome. In a second study, subjects were interviewed about various aspects of coin flipping. Many gave contradictory answers to closely related questions. We offer two explanations for inconsistent responses: a) switching among incompatible perspectives of uncertainty, including the outcome approach, judgment heuristics, and normative theory, and b) reasoning via basic beliefs about coin flipping. As an example of the latter explanation, people believe both that a coin is unpredictable and also that certain outcomes of coin flipping are more likely that others. Logically, these beliefs are not contradictory; they are, however, incomplete. Thus, contradictory statements appear when these beliefs are applied beyond their appropriate domain.

Laboratory experiments using spectrophotometers and pH meters were incorporated into an undergraduate introductory statistics course in order to create an interdisciplinary approach of teaching statistics to non-statistics majors. By conducting laboratory experiments commonly associated with science-based curricula, students were exposed to the relationship between science and statistics through experimental design and data analysis. The laboratory experiments used in the course are related to fields such as chemistry, biology, and environmental sciences and are described in this article.