# Module 1 Introduction to Exploratory Factor Analysis

**Overview**

In Module 1, you will learn about the theoretical underpinnings of exploratory factor analysis (EFA), when to use EFA, the type of research question and data necessary for EFA, factor extraction method and choosing the appropriate extraction method.

**Student Learning Objectives**

At the end of this Module, students will be able to:

- Understand the fundamental concept of EFA
- Formulate appropriate research questions/hypotheses that EFA can answer
- Choose appropriate data for EFA
- Distinguish between factor extraction methods
- Choose the appropriate extraction methods

Exploratory factor analysis (EFA) is a technique used to explore the structure, pattern, or dimension of a set of observed variables. This technique identifies and examines the number of observed variables that form clusters called factors, constructs, or latent variables. EFA is a data reduction technique that helps researchers reduce data complexity and provide insight into the underlying dimension of the data.