Statistics for Evidence-Based Practice and Evaluation

Rubin (U. of Texas at Austin) introduces undergraduate and graduate students in the helping professions to understanding and using statistics in evidence-based practice. After discussing the value and relevance of statistics and an overview of evidence-based practice, he reviews basic research methods and terms, then the reduction, presentation, and analysis of data for descriptive purposes. He also reviews understanding inferential data analysis and concepts like probability, sampling error, theoretical sampling distributions, the null hypothesis, and statistical conclusion validity. He then explains different inferential statistical procedures and applies material to the analysis of data in single-system evaluations. He discusses both formulas and calculations and meanings and applications of statistics, but separates the mathematical material from the narrative through boxes, tables, and figures. He presents many different types of practice illustrations, and provides a simulated data set for an evaluation of a fictional residential treatment center. He uses SPSS software, but discusses it mostly in an appendix. This edition has more emphasis on distributions that are not normal, more content on calculating the Cohen's d effect size statistic, expanded coverage of t-Tests, updated SPSS material, coverage of multilevel modeling and structural equation modeling in the appendices, and a separate workbook to accompany the text. Annotation c2012 Book News, Inc., Portland, OR (booknews.com)