Teaching

  • The 1970 draft lottery for birthdates is reviewed as an example of a government effort at randomization whose inadequacy can be exhibited by a wide variety of statistical approaches. Several methods of analyzing these data -- which were of life-and-death importance to those concerned -- are given explicitly and numerous others are cited. In addition, the corresponding data for 1971 and for 1972 are included, as are the alphabetic lottery data, which were used to select draftees by the first letters of their names. Questions for class discussion are provided. The article ends with a survey of primary and secondary sources in print.

  • We describe a Java applet that allows users to see and learn the fitting of regression models in a manner that is both visual and interactive, as well as consonant for linear and nonlinear models. In addition, this program familiarizes users with the fact that many different parameterizations exist for a single function, and it provides insight about the relationship between these models. Called Visual Fit, this program draws scatterplots of data and allows users to fit various nonlinear models to the data. The program can also provide least squares estimates or true population parameters for comparison with the estimates made by the user. We discuss what types of parameters can be represented in a visually obvious way and which cannot. Visual Fit may be useful for both introductory statistics classes and higher-level courses. Visual Fit is available at http://www.amstat.org/publications/jse/secure/v7n2/visualfit.html

  • Given the emphasis on utilizing the computer in many statistics courses, we discuss how we have implemented microcomputer task based testing in our courses. Background information is provided about a required, undergraduate, multiple section course, and why we believe computer-based testing is an effective evaluation instrument. Issues of examination design, administration, and evaluation are presented. Examples of problems used in computer-based exams are also included.

  • In this second paper of a series, two programs for EGA-equipped IBM-PC compatible machines are included with indications of their pedagogical uses in the teaching of elementary probability and statistics. Concepts illustrated include the coefficient of correlation, the expectation of a discrete distribution, the concept of a fair game, and the hypergeometric distribution. Three datasets useful for illustrating correlation are also documented and appended.

  • The aim of this paper is to draw to the attention of statisticians teaching business students three substantial computer simulations, the single objective of which is profit maximization. It is believed that in pursuing this purely business objective, students gain a better understanding of the need for and utility of statistical methods for research, analysis, and forecasting. The full text of these simulations and the associated computer programs, teaching notes, and sample student responses may be freely downloaded and used for classroom purposes.

  • The advent of electronic communication between students and teachers facilitates a number of new techniques in the teaching of statistics. This article presents the author's experiences with providing each student in a large, multi-section class with a unique dataset for homework and in-class exercises throughout the semester. Each student's sample is pseudo-randomly generated from the same underlying distribution (in the case of hypothesis tests and confidence intervals involving ), or the same underlying linear relationship (in the case of simple linear regression). This approach initially leads students to identify with their individual summary statistics, test results, and fitted models, as "the answer" they would have come up with in an applied setting, while subsequently forcing them to recognize their answers as representing a single observation from some larger sampling distribution.

  • This article presents the use of an interesting consulting problem as a practical exercise for a basic course in statistics for engineering students. The consulting problem considered is the estimation of the reliability of the Spanish power generating system. We have used this problem to illustrate the distribution of sums of random variables, the central limit theorem and its limitations, and other issues. We have also designed a practical exercise to show the students the use of Monte Carlo simulation to solve part of the statistical problem.

  • Many widely-adopted college textbooks that are designed for a student's first (and possibly last) statistics course have incorporated new trends in statistical education, but are organized in a manner that is still driven by a traditional computational, rather than a conceptual, framework. An alternative approach allows for the treatment of many seemingly-unrelated conventional procedures such as one- and two-sample t-tests and analyses of variance and covariance under a unifying prediction model approach. Furthermore, this approach, combined with the power of modern statistical software packages, prepares the student to solve problems beyond the scope of traditional procedures. Students will appreciate the acquisition of practical research capabilities and might even be stimulated to continue their study of statistics.

  • Basic probability concepts are difficult for some students to understand initially. Through the use of a Venn diagram disguised as a pizza, we will discuss how to explain introductory probability concepts. Students are able to answer probability questions, including conditional probability, by simply looking at a picture. This tool not only enhances learning but retention as well.

  • Well-defined measures of performance are readily available for baseball players, making the modeling of their salaries a popular statistical exercise. In this article, the salaries for non-pitchers for the 1992 Major League Baseball season are provided, along with numerous measures of the players' previous year's performances. Also included are indicators of each player's ability to switch teams. This dataset is useful in upper-division regression analysis courses because it exhibits many "real world" difficulties that can be remedied using techniques outlined in the course.

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