Examine interpretation issues relevant to quantitative data analysis, including randomization, sample size, statistical versus practical significance, cultural bias, generalizability, and options for reporting quantitative results, such as effect sizes and variance accounted for, replication, use of nonparametric statistics, exploration of competing explanations, recognition of a study’s limitations, principled discovery strategy, and effect sizes.