Journal Article

  • Students of all ages seem fascinated by the lottery, making it a ready tool for illustrating basic probabilistic concepts. The author has developed a program called "Lotto Luck" for IBM PC compatibles which has been used on over 100 classrooms from grades 6 through 12 and with dozens of college classes and civic groups to demonstrate what happens to the "earnings" of the frequent lottery player over a period of time. We discuss how to use the program and provide information for obtaining the complied code by ftp.

  • While many teachers of statistics are likely to focus on transmitting knowledge, many students are likely to have trouble with statistics due to non-cognitive factors, such as negative attitudes or beliefs towards statistics. Such factors can impede learning of statistics, or hinder the extent to which students will develop useful statistical intuitions and apply what they have learned outside the classroom. This paper reviews the role of affect and attitudes in the learning of statistics, critiques current instruments for assessing attitudes and beliefs of students, and explores assessment methods teachers can use to gauge students' dispositions regarding statistics.

  • This review grows out of a strong conviction on three points: 1. Statistics is fundamentally and primarily concerned with analyzing real data. 2. Data analysis, including inference, is both intellectually challenging and intrinsically interesting. 3. Until recently, most authors of introductory statistics textbooks have managed to do a superb job of concealing from their readers the truth of the first two points. Fortunately, the last decade has seen the arrival of a number of innovative introductory textbooks, so I now find it much more reasonable than in the past to apply high standards in judging an elementary book. In preparing this review, I have tried to present these standards systematically; I use them as an organizing frame for comparing 11 new books (or new editions) with 5 favorites from the past 10 years.

  • Although the use of software has become widespread in elementary statistics courses, there has been little formal evaluation of its effectiveness. In this experiment with the use of software, primarily for simulations in an introductory statistics course, effectiveness was measured in two ways: whether students did better on examinations and whether they believed that the software was useful. Results showed that students did significantly better on the examinations and that about half of them considered the software to be useful. However, even among those who believed that the software was helpful, many objected to the extra time involved.

  • In their article Ayton, Hunt and Wright address a number of issues that impinge on the concept of randomness. They appear to question not only the methodological soundness and general implications of research on "misconceptions" in statistics, but also the soundness of aspects of statistical inference. We concentrate here on a few key issues about which we are in disagreement (we think) with the authors.

  • Regardless of the level of sophistication of one's students, or the exact content of one's course, it is important to think broadly about the general messages one wishes to convey, and then to formulate a number of explicit goals one would like to achieve in teaching statistics to sociology students. Five such goals are discussed: 1) overcoming fears, resistances, and tendencies to overmemorize; 2) the importance of intellectual honesty and integrity; 3) understanding the relationship between deductive and inductive inferences; 4) learning to play the role of reasonable critic; and 5) learning to handle complexities in a systematic fashion. Illustrative examples are given to show how exercises can be tailored to the course's contents and the level of student backgrounds.

  • This article described three heuristics that are employed in making judgments under uncertainty: (i) representativness, which is usually employed when people are asked to judge the probability that an object or event A belongs to class or process B; (ii) availability of instances or scenarios, which is often employed when people are asked to assess the frequency of a class or the plausibility of a particular development; and (iii) adjustment from an anchor, which is usually employed in numerical prediction when a relevant value is available. These heuristics are highly economical and usually effective, but they lead to systematic and predictable errors. A better understanding of these heuristics and of the biases to which they lead could improve judgments and decisions in situations of uncertainty.

  • This paper is concerned with a general education course in elementary statistics, a course which is open to students of all disciplines. This provides an interesting mix of student interests. Some of the students are very familiar with the use of technology, having personal computers in their homes which they use on a frequent basis. Other students have never touched a computer and suffer a great deal of anxiety at the mere thought of using this technology. The curriculum must be designed to appeal to both types of students.

  • This paper proposes a framework for the development of instruments to measure content learning and problem-solving skills for the introductory statistics course. This framework is based upon a model of the problem-solving process central to statistical reasoning. The framework defines and interrelates six measurement tasks: (1) subjective reports; (2) reports concerning truth, falsity, or equivalence; (3) supply the appropriate missing information in a message; (4) answer a question based upon a specific message; (5) reproduce a message; and (6) carry out a procedure.

  • A method is suggested to incorporate instruction in the concept and the application of power considerations into an applied statistics course. This is based on designing one table usable for a wide range of the type of statistical tests usually introduced in such a course.

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