General Linear Modelling

Welcome to General Linear Modeling (GLM) and Generalized Linear Modeling (GLIM), a comprehensive introductory course designed to help you understand two of the most important statistical modeling frameworks used in modern data analysis. Whether you are a student, researcher, academic, or data analyst, this course provides a strong conceptual foundation for understanding when and how these techniques are applied in research and industry.

The course introduces the principles of General Linear Models (GLM) and Generalized Linear Models (GLIM), explaining their purpose, underlying assumptions, and practical applications. You will explore the differences between the two modeling approaches, learn how to select the appropriate model for different types of data, and gain an understanding of exponential family distributions and their role in generalized linear modeling. Through clear explanations and practical examples, the course helps build the theoretical knowledge required before applying these techniques using statistical software.

By the end of this course, you will have a solid understanding of GLM and GLIM concepts, enabling you to identify the appropriate modeling approach for various research problems and build a strong foundation for advanced statistical analysis.