interaction effect

Terms from Statistics for HCI: Making Sense of Quantitative Data

In an ANOVA the interaction effect is the measured effect where two or more of the factors have a complex behaviour over and above the main effect of each.
For example, suppose we have measured the following error rates (averaged over many replications, and assuming equal numbers of replication in each cell):
system A system B
novice 70 50
expert 10 30
There is an interaction effect of magnitude +/10, whereby novices on system A and experts on system B perform 10 points higher than one might expect based on the main effects for the expertise and system, and novices on system B and experts on sysem A perform 10 points lower than expected.

Used in Chap. 14: page 171

Also used in hcistats2e: Chap. 12: page 138

Used in glossary entries: ANOVA (Analysis of Variance), main effect