Data Analysis for Experimental Design

This engaging text shows how statistics and methods work together, demonstrating a variety of techniques for evaluating statistical results against the specifics of the methodological design. Richard Gonzalez elucidates the fundamental concepts involved in analysis of variance (ANOVA), focusing on single degree-of-freedom tests, or comparisons, wherever possible. Potential threats to making a causal inference from an experimental design are highlighted. With an emphasis on basic between-subjects and within-subjects designs, Gonzalez resists presenting the countless exceptions to the rule that make many statistics textbooks so unwieldy and confusing for students and beginning researchers. Ideal for graduate courses in experimental design or data analysis, the text may also be used by advanced undergraduates preparing to do senior theses. Useful pedagogical features include: *Discussions of the assumptions that underlie each statistical test *Sequential, step-by-step presentations of statistical procedures *End-of-chapter questions and exercises *Accessible writing style with scenarios and examples *A companion Web page (www.umich.edu/~gonzo/daed) offering data and syntax files in R and SPSS for the research examples used in the book, a short guide to SPSS syntax, and detailed course notes on each of the book's topics.