This paper, presented at a conference of college admissions counselors, attempts to provide a brief overview of descriptive and inferential statistics for college admissions officers, in the hopes that it will encourage these admissions personnel to question assumptions more critically. The paper begins by defining statistics, specifically…

Various statistical methods have been available to deal with missing data problems, but the difficulty is that they are based on somewhat restrictive assumptions that missing patterns are known or can be modeled with auxiliary information. This paper treats the presence of missing cases from the viewpoint that generalization as a sample does not…

The distinction between Type 1 and Type 12 sampling in connection with measurement data is discussed, and a method is presented for simulating data arising from Type 12 sampling. A Monte Carlo study is described that shows conditions under which precise confidence level control under Type 12 sampling is maintained. (SLD)

Shows how to extend the inferential test of B. Shipley (2000), which is applicable to recursive path models without correlated errors, to a class of recursive path models that includes correlated errors. Discusses when the extended model is and is not superior to classical structural equation modeling. (SLD)

The finite intersection test (FIT) developed by P. K. Krishnaiah (1964, 1965) is discussed and compared with more familiar methods for simultaneous inference. How the FIT can be used to analyze differences among all means for both univariate and multivariate experimental designs is explained. (SLD)

The national lottery is often portrayed as a game of pure chance with no room for strategy. This misperception seems to stem from the application of probability instead of expectancy considerations, and can be utilized to introduce the statistical concept of expectation.

The increased use of effect sizes in single studies and meta-analyses raises new questions about statistical inference. Choice of an effect-size index can have a substantial impact on the interpretation of findings. The authors demonstrate the issue by focusing on two popular effect-size measures, the correlation coefficient and the…

The Behrens-Fisher problem arises when one seeks to make inferences about the means of two normal populations without assuming the variances are equal. This paper presents a review of fundamental concepts and applications used to address the Behrens-Fisher problem under fiducial, Bayesian, and frequentist approaches. Methods of approximations to…

In rebuttal to a critique of the authors' examination of prevalence rate variability for special education categories, it is claimed that a consideration of the nature of prevalence rate data, the correct use of inferential statistics, and the coefficient of variation itself, suggest the objections are not justified. (Author/DB)

Presents an overview of a wide range of measurement models currently available to the analyst who needs to make accurate and valid inferences about respondents and stimuli from data. Reviews models with and without predictor variables or observed and latent predictors, as well as parametric and nonparametric models, and models for order-restricted…

Describes uses of statistical research tools: descriptive statistics, correlation, regression, and inferential statistics. Addresses concerns about statistical analysis in agricultural research. (SK)

The APA Task Force on Statistical Inference recently recommended reporting effect sizes alongside results of statistical significance tests. The purpose of this article is to investigate effect size usage in gifted education research and to follow up on a similar investigation published by Plucker (1997). A content analysis of effect size…

This article describes an illustration of Bayesian inference that has proved popular with students.

The authors provide generalizations of R. J. Boik's (1993) studentized maximum root (SMR) procedure that allow for simultaneous inference on families of product contrasts including simple effect contrasts and differences among simple effect contrasts in coherent analyses of data from 2-factor fixed-effects designs. Unlike the F-based simultaneous…

Regardless of the related discipline, students in statistics courses invariably have difficulty understanding the connection between the numerical values calculated for end-of-the-chapter exercises and their usefulness in decision making. This disconnect is, in part, due to the lack of time and opportunity to actually design the experiments and…