Applying Regression and Correlation
Purchase
Description
The authors start with the basics and begin by re-visiting the mean, and the standard deviation, with which most readers will already be familiar, and show that they can be thought of a least squares model. The book then shows that this least squares model is actually a special case of a regression analysis and can be extended to deal with first one, and then more than one independent variable.
Extending the model from the mean to a regression analysis provides a powerful, but simple, way of thinking about what students believe are the more complex aspects of regression analysis.
The authors gradually extend the model to include aspects of regression analysis such as non-linear regression, logistic regression, and moderator and mediator analysis. These approaches are often presented in terms that are too mathematical for non-statistically inclined students to deal with.
Throughout the book maintains a conceptual, non-mathematical focus. Most equations are placed in an appendix, where a detailed explanation is given, to avoid disrupting the flow of the main text.
This book will be indispensable for anyone using regression and correlation from undergraduates doing projects to postgraduate and researchers.
Contents
PART ONE: I NEED TO DO REGRESSION ANALYSIS TOMORROW
- Building Models with Regression and Correlation
- More Than One Independent Variable
- Multiples Regression
- Categorical Independent Variables
PART TWO: I NEED TO DO REGRESSION ANALYSIS NEXT WEEK
- Assumptions in Regression Analysis
- Issues in Regression Analysis
PART THREE: I NEED TO KNOW MORE OF THE THINGS THAT REGRESSION CAN DO
- Nonlinear and Logistic Regression
- Moderator and Mediator Analysis
- Introducing Some Advanced Techniques
- Multilevel Modelling and Structural Equation Modelling
Resources
Authors' home page including data sets used in the book
Description
The authors start with the basics and begin by re-visiting the mean, and the standard deviation, with which most readers will already be familiar, and show that they can be thought of a least squares model. The book then shows that this least squares model is actually a special case of a regression analysis and can be extended to deal with first one, and then more than one independent variable.
Extending the model from the mean to a regression analysis provides a powerful, but simple, way of thinking about what students believe are the more complex aspects of regression analysis.
The authors gradually extend the model to include aspects of regression analysis such as non-linear regression, logistic regression, and moderator and mediator analysis. These approaches are often presented in terms that are too mathematical for non-statistically inclined students to deal with.
Throughout the book maintains a conceptual, non-mathematical focus. Most equations are placed in an appendix, where a detailed explanation is given, to avoid disrupting the flow of the main text.
This book will be indispensable for anyone using regression and correlation from undergraduates doing projects to postgraduate and researchers.
Contents
PART ONE: I NEED TO DO REGRESSION ANALYSIS TOMORROW
- Building Models with Regression and Correlation
- More Than One Independent Variable
- Multiples Regression
- Categorical Independent Variables
PART TWO: I NEED TO DO REGRESSION ANALYSIS NEXT WEEK
- Assumptions in Regression Analysis
- Issues in Regression Analysis
PART THREE: I NEED TO KNOW MORE OF THE THINGS THAT REGRESSION CAN DO
- Nonlinear and Logistic Regression
- Moderator and Mediator Analysis
- Introducing Some Advanced Techniques
- Multilevel Modelling and Structural Equation Modelling
Resources
Authors' home page including data sets used in the book
Reviews
Applying Regression and Correlation
A Guide for Students and Researchers
March 2001 | 272 pages | Sage UK
| Format | Published Date | ISBN | Price |
|---|---|---|---|
| Paperback | 31/03/2026 | 9780761962304 | $122.00 |
| 180 Day Ebook | 28/03/2023 | 9781446232897 | $72.00 |
| Lifetime | 28/03/2023 | 9781446232897 | $104.00 |
The authors start with the basics and begin by re-visiting the mean, and the standard deviation, with which most readers will already be familiar, and show that they can be thought of a least squares model. The book then shows that this least squares model is actually a special case of a regression analysis and can be extended to deal with first one, and then more than one independent variable.
Extending the model from the mean to a regression analysis provides a powerful, but simple, way of thinking about what students believe are the more complex aspects of regression analysis.
The authors gradually extend the model to include aspects of regression analysis such as non-linear regression, logistic regression, and moderator and mediator analysis. These approaches are often presented in terms that are too mathematical for non-statistically inclined students to deal with.
Throughout the book maintains a conceptual, non-mathematical focus. Most equations are placed in an appendix, where a detailed explanation is given, to avoid disrupting the flow of the main text.
This book will be indispensable for anyone using regression and correlation from undergraduates doing projects to postgraduate and researchers.
Table Of Contents:
- PART ONE: I NEED TO DO REGRESSION ANALYSIS TOMORROW
- Building Models with Regression and Correlation
- More Than One Independent Variable
- Multiples Regression
- Categorical Independent Variables
- PART TWO: I NEED TO DO REGRESSION ANALYSIS NEXT WEEK
- Assumptions in Regression Analysis
- Issues in Regression Analysis
- PART THREE: I NEED TO KNOW MORE OF THE THINGS THAT REGRESSION CAN DO
- Nonlinear and Logistic Regression
- Moderator and Mediator Analysis
- Introducing Some Advanced Techniques
- Multilevel Modelling and Structural Equation Modelling