The theoretical reason for the presence of differential item functioning (DIF) is that data are multidimensional and two groups of examinees differ in their underlying ability distribution for the secondary dimension(s). Therefore, the purpose of this study was to determine how much the secondary ability distributions must differ before DIF is…

Correlated predictors in regression models are a fact of life in applied social science research. The extent to which they are correlated will influence the estimates and statistics associated with the other variables they are modeled along with. These effects, for example, may include enhanced regression coefficients for the other variables--a…

As a part of an opening course survey, data on eye color and gender were collected from students enrolled in an introductory statistics course at a large university over a recent four year period. Biologically, eye color and gender are independent traits. However, in the data collected from our students, there is a statistically significant…

This mixed-methods study reports psychometric properties of the 34-item Reasoning about P-values and Statistical Significance (RPASS) scale. RPASS is being designed as a research tool to assess effects of teaching methods on students' inferential reasoning. During development (Phase I), two graphical scenarios and 12 items were added to the scale,…

A common mistake in analysis of cluster randomized experiments is to ignore the effect of clustering and analyze the data as if each treatment group were a simple random sample. This typically leads to an overstatement of the precision of results and anticonservative conclusions about precision and statistical significance of treatment effects.…

This paper makes an econometric testing of one-minute paper used as a tool to manage and assess instruction in my statistics class. One of our findings is that the one minute paper when I have tested it by using an OLS estimate in a controlled Vs experimental design framework is found to statistically significant and effective in enhancing…

A common mistake in analysis of cluster randomized trials is to ignore the effect of clustering and analyze the data as if each treatment group were a simple random sample. This typically leads to an overstatement of the precision of results and anticonservative conclusions about precision and statistical significance of treatment effects. This…

Written by a social worker for social work students, this is a nuts and bolts guide to statistics that presents complex calculations and concepts in clear, easy-to-understand language. It includes numerous examples, data sets, and issues that students will encounter in social work practice. The first section introduces basic concepts and terms to…

A selection of statistical problems commonly encountered in psychological or psychiatric research concerning correlation coefficients are re-evaluated in the light of recently developed simplifications in the forms of the distribution theory of the intraclass correlation coefficient, of the product-moment correlation coefficient, and the Spearman…

The primary purpose of the present study was to investigate the appropriateness of several tests of significance for use with interrupted time series data. The second purpose was to determine what effect the violation of the assumption of uncorrelated error would have on the three tests of significance. The three tests were the Mood test,…

Data were analyzed to see if a correlation or relationship existed between students' grades in a course and students' rankings of the professor's teaching. Graphing calculators allowed students to visualize relationships between the data and to compute the equation of the regression line, compute the correlation coefficient, and test statistical…

This working paper contains the overheads used in a seminar designed to introduce some basic concepts of statistics to nonstatisticians. The seminar has been presented on several occasions. The first part of the seminar, and the first set of overheads, deals with the essentials of statistics, including: (1) population, sample, and inference; (2)…

This study guide presents lessons on hand calculating various statistics: Central Tendency and Dispersion; Tips on Data Presentation; Two-Tailed and One-Tailed Tests of Significance; Error Types; Standard Scores; Non-Parametric Tests such as Chi-square, Spearman Rho, Sign Test, Wilcoxon Matched Pairs, Mann-Whitney U, Kruskal-Wallis, and Rank Sums;…