W. Paul Vogt, PhD, until his death in 2016, was Emeritus Professor of Research Methods and Evaluation at Illinois State University, where he received both teaching and research awards. Dr. Vogt's areas of specialization included research design and data analysis, with particular emphasis on combining qualitative, quantitative, and graphic approaches. His books include Selecting the Right Analyses for Your Data and When to Use What Research Design.

Elaine R. Vogt, MA, CAS, is certified as a school psychologist in New York and Illinois and has worked as a psychologist in schools and a variety of other public and private institutions. She recently retired from Illinois Wesleyan University, where she taught piano and was a staff accompanist. Ms. Vogt's research interests include cognitive psychology, especially music cognition.

Dianne C. Gardner, PhD, is Associate Professor of Educational Administration and Foundations and a Research Associate at the Center for the Study of Education Policy at Illinois State University. Dr. Gardner's research interests include assessment, evaluation of collaborative professional learning systems, qualitative research methodology, and P-20 education systems. She serves as a program evaluator for state- and federally funded education programs.

Lynne M. Haeffele, PhD, is a Senior Research Associate at the Center for the Study of Education Policy at Illinois State University and also serves as Education Policy Director in the Office of the Illinois Lieutenant Governor. She provides research, evaluation, policy analysis, and management expertise for various state and federal projects in P-20 education, and has served as a consultant to the U.S. Department of Education. Dr. Haeffele's research interests include combining research designs, applying research findings to policy and practice, program evaluation, and the topical areas of college readiness and completion, organizational performance, and school-university partnerships.

Preface
General Introduction
I. Coding Data-by Design
1. Coding Survey Data
2. Coding Interview Data
3. Coding Experimental Data
4. Coding Data from Naturalistic and Participant Observations
5. Coding Archival Data
II. Analysis and Interpretation of Quantitative Data
6. Describing, Exploring, and Visualizing Your Data
7. What Methods of Statistical Inference to Use When
8. What Associational Statistics to Use When
9. Advanced Associational Methods and Analyses
10. Model Building and Selection : Quantitative Data
III. Analysis and Interpretation of Qualitative and Combined/Mixed Data
11. Inductive Analyses of Qualitative Data: Ethnographic Approaches and Grounded Theory
12. Deductive Analyses of Qualitative Data: Comparative Case Studies and Qualitative Comparative Analysis
13. Coding and Analyzing Data from Combined and Mixed Designs
14. Conclusion