Linear Regression by Peter Martin

Linear Regression by Peter Martin

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.

Martin provides a comprehensive account of linear regression and offers a detailed and practical guide on how to interpret all the coefficients and statistics included in a model - a valuable resource for social scientists at all stages in their careers

-- Jane Elliott

The first five chapters set up a clear and solid foundation for understanding statistical models covering a clear explanation of linear regression and its assumptions, the indicators of model fit and predictive power, methods for comparing models with one another as well as complicated cases involving interactions and transformed predictor variables. The final chapter, named ‘Where to Go From Here’, suggests some ways in which the reader could deepen their knowledge of regression, and includes the exploration of some paths that could be taken when/if linear regression is not a suitable model. This book is clearly written and accessible to anyone who has previous basic knowledge of descriptive and inferential statistics. Not only does it include flawless text and graphical explanations, but it is also linked with a support website that supplies data sets for most of the examples used. A big plus is the companion examples/exercises for the open-source software R.

-- Antonella Cirasola
This is an excellent introductory text to multivariate analysis of data and is written in accessible language. This text introduces linear regression in a way that is accessible for those with knowledge of descriptive and inferential statistics. The text brings statistical modelling to life while capturing the messiness and ambiguity we may face when interpreting real data. It is engaging and easy to follow. I would highly recommend this for social scientists with an interest in linear regression. -- Dr Sally O′Keeffe

This is a must-have resource for people looking for a clear and complete overview of linear regression. There are many books on the topic but Peter Martin’s Linear regression: an introduction to statistical models is among the few that provided me with a crystal-clear explanation of the technique with real research examples. Additionally, the book deals in detail with an often-overlooked aspect of this type of regression: its assumptions. Running a model can be straightforward, but the author is right to remind us that the results can be misleading if the assumptions of the technique are not assessed. The engaging narrative makes this book welcoming to those without a solid statistical background, but it is still able to provide very relevant insights for the more mathematically inclined.

-- Eliazar Luna

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.

SKU	Nicht verfügbar
ISBN 13	9781526424174
ISBN 10	1526424177
Titel	Linear Regression
Autor	Peter Martin
Serie	The Sage Quantitative Research Kit
Buchzustand	Nicht verfügbar
Bindungsart	Paperback
Verlag	Sage Publications Ltd
Erscheinungsjahr	2022-03-21
Seitenanzahl	200
Hinweis auf dem Einband	Die Abbildung des Buches dient nur Illustrationszwecken, die tatsächliche Bindung, das Cover und die Auflage können sich davon unterscheiden.
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