Applied Regression Analysis

Christer Thrane holds a Ph.D. in Sociology and is Professor at Inland Norway University of Applied Sciences. His research interests include quantitative modeling studies in leisure, recreation, sports and tourism. He has 25 years of experience in teaching quantitative research methods and regression analysis.

• Part 1: The Basics 1. What is regression analysis? 2. Linear regression with a single independent variable 3. Linear regression with several independent variables: Multiple regression Part 2: The Foundations 4. Samples and populations, statistical uncertainty and testing of statistical significance 5. The assumptions of regression analysis Part 3: The Extensions 6. Beyond linear regression: Non-additivity, non-linearity and mediation 7. A categorical dependent variable: Logistic (logit) regression and related methods 8. An ordered (ordinal) dependent variable: Logistic (logit) regression 9. The quest for a causal effect: Instrumental variable (IV) regression Part 4: Regression Purposes, Academic Regression Projects and the Way Ahead 10. Regression purposes in various academic settings and how to perform them 11. The way ahead: Related techniques

“This book finds a rare balance between applied statistical analysis and theory, giving students the confidence to apply regression analysis in their projects, while being aware of the potential pitfalls.” — Johan A. Elkink, Associate Professor in Social Science Research Methods, University College Dublin, Ireland“This book provides a short and bright path to understand the meaning and usefulness of regression analysis. If you are a student or policy maker with limited econometrics skills this book equips you with the right and sufficient skills.” — Dr. Maty Konte, United Nations University