The Mahalanobis distance model was compared with the linear discriminant function model and found to provide very similar results, even when a number of the variables were binary. A group of college freshmen were categorized into two groups: 116 "leavers," students who did not return for the second year, and 269 "returners."…

The Chi-Square Test for Hierarchical Dependency (THD) is presented. The THD tests the hypothesis that all members of a population who possess a certain skill are a subset of the members who possess another skill. This hypothesis is basic to the writings of several prominent theorists, such as Gagne and Piaget. The THD is designed as an improvement…

Checking of parametric assumptions is an often ignored step in the inferential process. A misconception regarding symmetry (one aspect of "robustness") is prevalent: that in nonsymmetric distributions the mean and median are always non-coincidental. It is to this fallacious point that the discussion is directed. A generally accepted index of…

This paper presents three examples of nonparametric statistical tests that can aid certain decision-making processes in the community college by using basic student data to separate "scientific" decision-making from "opinion" decision-making. A brief example of each test in a decision-making situation is related to illustrate…

Advocates the use of nonparametric techniques, when teaching data analysis to undergraduate life-science students, to circumvent their poor mathematical training. (GA)

A method for ordering persons and items when all responses are ordinal was developed and applied to several sets of questionnaire data (from undergraduates) and one set of archeological data. The method provides a possible nonparametric treatment of data usually treated by more traditional psychometric methods. (SLD)

This paper explains how to combine probabilities from discrete distributions, such as probability distributions for nonparametric tests. (Author/BW)

This paper traces the course of the consequences of viewing test responses as simply providing dichotomous data concerning ordinal relations. It begins by proposing that the score matrix is best considered to be items-plus-persons by items-plus-persons, and recording the wrongs as well as the rights. (Author/CTM)

Monte Carlo research with TAILOR, a program using implied orders as a basis for tailored testing, is reported. TAILOR typically required about half the available items to estimate, for each simulated examinee, the responses on the remainder. (Author/CTM)

Three nonparametric alternatives to the parametric Bartlett test are presented for handling the K-sample equality of variance problem. The two-sample Siegel-Tukey test, Mood test, and Klotz test are extended to the multisample situation by Puri's methods. These K-sample scale tests are illustrated and compared. (Author/GDC)

A problem of considerable importance in certain educational settings is determining how many items to include on a mastery test. Applying ranking and selection procedures, a solution is given which includes as a special case all existing single-stage, non-Bayesian solutions based on a strong true-score model. (Author/JKS)

Pre-written, supporting conversational programs written in BASIC are available for use in introductory statistics courses designed for college undergraduates and high school seniors. (MM)

Discusses the application of the Kolmogorov-Smirnov two-sample tests, as an alternative to the Chi-square test, for survey research problems in business education and includes a computer program written for the convenience of researchers. The two-sample test is recommended for differentiating independent distributions. (MF)

The power of the nonparametric person-fit statistic, U3, is investigated through simulations as a function of item characteristics, test characteristics, person characteristics, and the group to which examinees belong. Results suggest conditions under which relatively short tests can be used for person-fit analysis. (SLD)

A study of the ability of different models--including the classification techniques of discriminant analysis, logistic regression, and neural networks--to predict the academic success of master's degree students in business administration suggests that prediction is difficult, but that classification and nonparametric techniques may be…