A Guide to Linear Regression for Thesis Writing in Social Sciences

Linear regression analysis is one of the most widely utilized statistical procedures in social sciences. It also serves as the building block for other statistical procedures such as moderation and mediation analysis. Despite its significance, many social scientists struggle to understand the complexities of this procedure, especially if they lack a significant statistical background. Existing literature on the topic can be overly complex and written for a target audience of mathematical statisticians, making it difficult for social scientists to consume and understand.

To help address this issue, a new book has been developed that presents the dynamics of linear regression analysis in a simplified and easy-to-understand manner. The book focuses on practical applications of linear regression analysis, starting with an explanation of the need for linear regression analysis in a thesis.

The book covers the different types of linear regression analyses and provides a typical SPSS output for linear regression analysis, accompanied by detailed statistical interpretations of the findings. In addition, the book addresses the challenges social scientists may face when performing linear regression analysis and when writing up and defending their analysis.

With its simplified language and straightforward approach, this book makes it easy for social scientists to understand the fundamental principles of linear regression analysis, regardless of their statistical background. By providing practical applications of linear regression analysis in social sciences, this book is an indispensable resource for researchers, students, and educators seeking to incorporate linear regression analysis into their research projects or theses.