Linear Regression: An Introduction to Statistical Models: The SAGE Quantitative Research Kit
Autor Peter Martinen Limba Engleză Paperback – 20 mar 2022
- Deciding the most appropriate model to use for your research
- Conducting simple and multiple linear regression
- Checking model assumptions and the dangers of overfitting
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Specificații
ISBN-13: 9781526424174
ISBN-10: 1526424177
Pagini: 200
Dimensiuni: 170 x 242 x 17 mm
Greutate: 0.33 kg
Ediția:1
Editura: SAGE Publications
Colecția Sage Publications Ltd
Seria The SAGE Quantitative Research Kit
Locul publicării:London, United Kingdom
ISBN-10: 1526424177
Pagini: 200
Dimensiuni: 170 x 242 x 17 mm
Greutate: 0.33 kg
Ediția:1
Editura: SAGE Publications
Colecția Sage Publications Ltd
Seria The SAGE Quantitative Research Kit
Locul publicării:London, United Kingdom
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Recenzii
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.
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.
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.
Cuprins
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
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
Notă biografică
Peter Martin worked as a professional civil engineer for over 50 years starting in the days when calculations were carried out with the aid of slide rules and 7-figure log tables. During his career he designed and supervised construction of many bridges and harbour works in the UK and throughout the Far East, SE Asia, and Africa, living in the East with his family for 12 years. He has three grown-up sons and six grandchildren and now lives in a village near Glasgow where he attempts to keep the garden in some sort of order.
Descriere
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.