Description

Book Synopsis
This book takes a fresh look at applying regression analysis in the behavioural sciences by introducing the reader to regression analysis through a simple model-building approach.

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 ar

Trade Review
`An excellent book on regression and correlation, which should be on the shopping list of all researchers in psychology and also of many psychology students′ - Statistical Methods in Medical Research

"This book is a gem. I would certainly recommend it to my students."

-- David Clark-Carter

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

Applying Regression and Correlation

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    A Paperback / softback by Jeremy Miles, Mark Shevlin

    £101.20

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    Order before 4pm today for delivery by Fri 27 Nov 2026.

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      Book details

      Publisher Sage Publications
      Published 24 November 2000
      ISBN-13 9780761962304
      978-0761962304
      ISBN-10 0761962301

      Description

      Book Synopsis
      This book takes a fresh look at applying regression analysis in the behavioural sciences by introducing the reader to regression analysis through a simple model-building approach.

      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 ar

      Trade Review
      `An excellent book on regression and correlation, which should be on the shopping list of all researchers in psychology and also of many psychology students′ - Statistical Methods in Medical Research

      "This book is a gem. I would certainly recommend it to my students."

      -- David Clark-Carter

      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

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