Linear Regression

In this engaging and well-illustrated volume of the SAGE Quantitative Research Kit, Peter Martin helps you make the crucial steps towards mastering multivariate analysis of social science data, introducing the fundamental linear and non-linear regression models used in quantitative research. The author covers both the theory and application of statistical models, with the help of illuminating graphs.

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.

  Autorentext

  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.

  Inhalt

  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