As a tour de force, data mining is likely to gain wider use in the next few years. To facilitate this transition, we make several recommendations addressed to both institutional research professionals and the Association of Institutional Research.

The ultimate goal of the institutional researcher is not always to test a research hypothesis, but more often simply to find an appropriate model to gain an understanding of the underlying characteristics and interrelationships of the data. Exploratory data analysis provides a means of accomplishing this. (Author)

Using data from a sales campaign for the Arizona State lottery, a multiplist strategy of program evaluation is analyzed. Several complementary designs are used within the strategy to help remove threats to internal validity associated with the nonequivalent control group design. (SLD)

Presents a classroom technique for demonstrating the post-factum interpretation problem. Describes the various ways that students interpreted data concerning the percentage of men and women in traditionally female occupations. Discusses the various uses of this technique in both introductory and research classes. (KO)

Using data for school reform is like painting a series of pictures--pictures that are subtle and capture the nuances of the subject. This is a far cry from drawing stick figures or paint-by-numbers. Imagine the experiences of the French painter Claude Monet as he wandered through his garden at Giverny at different times of the day and year,…

This lesson plan is designed to enable a student, after 50 minutes of instruction, to define the single sample chi-square test and explain the three conditions necessary to its proper use and the purpose of using it. The student will also be able to calculate and apply the single sample chi-square test in class according to the five steps with the…

Exploratory data analysis (EDA) gives students a feel for the data being considered. Four applications of EDA are discussed: the use of displays, resistant statistics, transformations, and smoothing. (RM)

Using the split-middle methods of trend estimation, evaluates the accuracy of interpretation of single subject data by comparing raters' visual analysis of behavior change with statistical determination of behavior change. Results indicate visual analysis accuracy was less than chance. Rater and student characteristics largely did not affect the…

In a study of the relationship between moral reasoning and teenage drug use, problems arose in an attempt to reduce qualitative data to a quantitative format: (1) making analytic sense of singular and universal responses; (2) the mistaken logical inference that each pattern of judgment should have behavioral indicators; and (3) construction and…

A study compared the influence of four missing data techniques on three published analyses of the High School and Beyond data (reexamining public- versus private-school achievement). Results indicated that use of data-replacement techniques affected the conclusions of the three studies examined. A small positive effect favoring private schooling…

Students at the middle school level are expected to use appropriate tools and techniques, including mathematics and graphing, to analyze and interpret data and communicate experimental findings. Measures of central tendency (mean, median, and mode--see sidebar for definitions) are often used as descriptive statistics when students conduct…

Education statistics are rarely neutral; those who collect and analyze them have different purposes. In this article, Bracey discusses several principles of data interpretation to help educators avoid falling into statistical traps. For example, because such reports as A Nation At Risk contain many "selected, spun, distorted, and even manufactured…

The data collected in higher education research are not always quantitative or continuous. Statistical methods using the log-linear model provide the institutional researcher with a powerful set of tools for addressing research questions when data are categorical. (Author/MSE)

Path analysis and linear structural relations (LISREL) provide the institutional researcher with some extremely powerful statistical tools. However, they must be applied and interpreted carefully with a full understanding of their limitations and the statistical assumptions on which they are based. (Author)

Maintains that usual method of analyzing student evaluation of teaching (SET) data is inappropriate. Shows results of both ordinary least squares (OLS) and multinominal logit data analysis approaches on 6,872 student evaluation of economics faculty at University of California, Santa Barbara during the 1983-84 academic year. Results show…