Related Experiment Video
Updated: Jun 15, 2026

A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments
Published on: March 1, 2022
Equivalence class formation: a method for teaching statistical interactions
Lanny Fields1, Robert Travis, Deborah Roy
1Graduate Center of The City University of New York, and Department of Psychology, Queens College/CUNY, 65-30 Kissena Boulevard, Flushing, New York 11367, USA. Lanny.Fields@QC.cuny.edu
Abstract:
Many students struggle with statistical concepts such as interaction. In an experimental group, participants took a paper-and-pencil test and then were given training to establish equivalent classes containing four different statistical interactions. All participants formed the equivalence classes and showed maintenance when probes contained novel negative exemplars. Thereafter, participants took a second paper-and-pencil test. Participants in the control group received two versions of the paper-and-pencil test without equivalence-based instruction. All participants in the experimental group showed increased paper-and-pencil test scores after forming the interaction-indicative equivalence classes. Class-indicative responding also generalized to novel exemplars and the novel question format used in the paper-and-pencil test. Test scores did not change with repetition for control group participants. Implications for behavioral diagnostics and teaching technology are discussed.
Related Concept Videos
Test for Homogeneity
Two-Way ANOVA
The two-way ANOVA analysis initially begins by stating the null hypothesis that there is an interaction effect between the two factors of a dataset. This effect can be visualized using line segments formed by joining the means for...
Bioequivalence Data: Statistical Interpretation
Introduction to Statistics
In statistics, the collection of individuals or objects under study is called population. The idea of sampling is to select a portion of the larger population...
F Distribution
Introduction to Test of Independence
The test statistic for a test of independence is similar to that of a goodness-of-fit test:
