This program focuses on teaching methods of analyzing quantitative data. Research typically begins with some form of measurement. Researchers may measure classroom learning, world knowledge, attitudes, goals, motivation orientations or personality.

Researchers must verify that their measures are reliable and valid and may use analytic techniques such as classical test theory or item response theory. Researchers submit their data to statistical techniques, such as analysis of variance (ANOVA), regression, structural equation modeling (SEM) and growth curve modeling, to pinpoint reliable patterns in the data and to verify whether groups differ in their outcomes.