Literature Index

Previous research has linked perfectionism to anxiety in the statistics classroom and academic performance in general. This article investigates the impact of the individual components of perfectionism on academic performance of students in the statistics classroom. The results of this research show a clear positive relationship between a studentÅfs personal standards and academic performance consistent with the literature. Surprisingly, the inherent need of some students for organization and structure was found to be negatively related to academic performance. This finding suggests that the organization of statistics as perceived by some students may not always foster understanding, resulting in student confusion and lack of achievement. This infers that statistics instructors may need to put sufficient emphasis on the underlying composition of statistical ideas and the linking of statistical techniques that are presented in the classroom and in the textbook. The implications of these results are discussed in terms of current trends in the reform of the statistics curriculum and approaches that may improve the clarity of the underlying structure of statistics.

Periodic regression is seldom included in syllabus of statistical courses. However, data following periodic or cyclic behavior are often encountered, especially in agriculture. Therefore, we think that this type of regression should be taught to students of agriculture, even in basic courses of statistics. In this paper we propose the way of teaching periodic regression through examples usually encountered in practice. The analysis of data will be based on the graphical interpretation, which would provide the visual display of the investigated problems as well.

The Pearson product moment (P.M.) correlation ("r") and four of its most widely used variations--the phi, the rho, the biserial, and the point-biserial coefficients--are reviewed. Using small data sets between one and nine, the conditions under which the various forms are restricted in power and robustness are explored. Seven sample data sets were constructed to illustrate the effects of the following conditions: (1) perfect correlation; (2) restriction of range; (3) measurement error (one variable); (4) measurement error (two variables); (5) extreme scores (one outlier); (6) extreme scores (two outliers); and (7) heterogeneity of sample distribution (one variable). Conceptual and algebraic linkages among the coefficients, and teaching practices that will facilitate the assimilation of these concepts and that will allow a student to predict the practical effects of the conditions are discussed. Two data tables are included. Appendix A contains definitions, formulas, and examples of the coefficients, which are presented as reproductions of a Macintosh computer hypercard stack designed for instructional purposes. Appendix B contains sample spreadsheet calculations for the seven conditions studied. (SLD)

A method that enables people to obtain the benefits of statistics and probability theory without the shortcomings of conventional methods because it is free of mathematical formulas and is easy to understand and use is described. A resampling technique called the "bootstrap" is discussed in terms of application and development. (KR)