Statistics for the Social Sciences A General Linear Model Approach

This chapter covers fundamental information that students must know in order to correctly conduct and interpret statistical analyses. The first section discusses why students in the social sciences need to learn statistics. The second section is a primer on the basics of research design, including the nature of research hypotheses and research questions, the difference between experimental and correlational research, and how descriptive statistics and inferential statistics serve different purposes. These foundational concepts are necessary to understand the rest of the textbook.

The final section of the chapter discusses the essential characteristics of models. Every statistical procedure creates a model of the data. Models are simplified versions of the world that make reality easier to understand. Fundamentally, all models are wrong, but the goal of scientists is to create models that are useful in explaining processes, making predictions, and building understanding of phenomena. The lesson distinguishes between theories, theoretical models, statistical models, and visual models so that students are equipped to deal with these concepts in later chapters.