Barbara G. Tabachnick is Professor Emerita of Psychology at California State University, Northridge, and co-author with Linda S. Fidell of Using Multivariate Statistics and Experimental Designs Using ANOVA . She has published over 80 articles and technical reports and participated in over 60 professional presentations, many invited.  She currently presents workshops in computer applications in univariate and multivariate data analysis and has consulted in a variety of research areas, including professional ethics in and beyond academia, effects of such factors as age and substances on driving and other performance, educational computer games, effects of noise on annoyance and sleep, and fetal alcohol syndrome.  She is the recipient of the 2012 Western Psychological Association Lifetime Achievement Award and a 2015 Western Psychological Association Presidential Citation.

Linda S. Fidell is Professor Emerita of Psychology at California State University, Northridge, and co-author with Barbara G. Tabachnick of Using Multivariate Statistics and Experimental Designs Using ANOVA . She has published several articles and given numerous professional presentations. She taught research design and statistics at CSUN for 32 years and retired in 2001. In 2015 she received a Western Psychological Association Presidential Citation. She now lives in Morro Bay, where she is delighted to contribute to the community. 

1. Introduction

2. A Guide to Statistical Techniques: Using the Book

3. Review of Univariate and Bivariate Statistics

4. Cleaning Up Your Act: Screening Data Prior to Analysis

5. Multiple Regression

6. Analysis of Covariance

7. Multivariate Analysis of Variance and Covariance

8. Profile Analysis: The Multivariate Approach to Repeated Measures

9. Discriminant Analysis

10. Logistic Regression

11. Survival/Failure Analysis

12. Canonical Correlation

13. Principal Components and Factor Analysis

14. Structural Equation Modeling by Jodie B. Ullman

15. Multilevel Linear Modeling

16. Multiway Frequency Analysis

17. An Overview of the General Linear Model

18. Time- ¿Series Analysis

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