This text introduces the fundamental linear regression models used in quantitative research. It covers both the theory and application of these statistical models, and illustrates them with illuminating graphs. The author offers guidence on:
- Deciding the most appropriate model to use for your research
- Conducting simple and multiple linear regression
- Checking model assumptions and the dangers of overfitting
Part of The SAGE Quantitative Research Kit, this book will help you make the crucial steps towards mastering multivariate analysis of social science data.
Table of Content
What is a statistical model
Simple linear regression
Assumptions and transformations
Multiple linear regression: A model for multivariate relationships
Multiple linear regression: Inference, assumptions, and standardization
Where to go from here
About the author
Dr Peter Martin is Lecturer in Applied Statistics at University College London. He has taught statistics to students of sociology, psychology, epidemiology, and other disciplines since 2003. One of the joys of being a statistician is that it opens doors to research collaborations with many people in diverse fields. Dr Martin has been involved in investigations in life course research, survey methodology, and the analysis of racism. In recent years his research has focused on health inequalities, psychotherapy, and the evaluation of healthcare services. He has a particular interest in topics around mental health.
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