On some history regarding statistical testing (C.J. Huberty, C.J. Pike). Five methodology errors in educational research: a pantheon of statistical significance and other faux pas (B. Thompson). Effect size measures: what they are and how to compute them (F.J. Kier). Relating variance partitioning in measurement analyses to the exact same process in substantive analyses (T.E. Dawson). Fixed-, random-, and mixed-effects ANOVA models: a user-friendly guide for increasing the generalizability of ANOVA results (B.N. Frederick). Factor scores and factor structure communality coefficients (R.D. Wells). Defining and interpreting suppressor effects: advantages and limitations (B.P. Lancaster. Why generalizability theory is essential and classical test theory is often inadequate (K.M. Kieffer). Item response theory: understanding the one-parameter Rasch model (C.E. Cantrell). Multivariatge normality: what is it and how is it assessed? (R.K. Henson). Strategies for detecting outliers in regression analysis: an introductory primer (V.P. Evans). Analyzing repeated measures designs using univariate and multivariate methods: a primer (J. Tanguma). New approaches to the analysis of repeated measurements (H.J. Keselman et al.). The simple difference score as an inherently poor measure of change: some reality, much mythology (B.D. Zumbo). Partitioning variance in the multivariate case: a step-by-step guide to canonical commonality analysis (B.N. Frederick). Acceptable variable deletion methods in canonical correlation analysis (C.E. Cantrell). Canonical redundancy (Rd) coefficients: they should (almost never) be computed and interpreted (J.K. Roberts).