This text takes a practical approach to multivariate data analysis, with an introduction to the most commonly encountered statistical and multivariate techniques. Using Multivariate Statistics provides practical guidelines for conducting numerous types of multivariate statistical analyses. It gives syntax and output for accomplishing many analyses through the most recent releases of SAS, SPSS, and SYSTAT, some not available in software manuals. The book maintains its practical approach, still focusing on the benefits and limitations of applications of a technique to a data set - when, why, and how to do it. Overall, it provides advanced students with a timely and comprehensive introduction to today's most commonly encountered statistical and multivariate techniques, while assuming only a limited knowledge of higher-level mathematics. Features and Benefits Each technique chapter discusses tests for assumptions of analysis (and procedures for dealing with their violation), presents a small example hand-worked for the most basic analysis, describes varieties of analysis, discusses important issues (such as effect size), provides an example with a real data set from tests of assumptions to write-up of a results section, and compares features of relevant programs. For each technique, an example with real data is provided, from assessment of assumptions to a Results section in APA format giving students a step-by-step algorithm for conducting an analysis and writing it up.