Exploratory Factor Analysis and How to do It?

Exploratory Factor Analysis and How to do It?

Exploratory factor analysis (EFA) is a statistical method that aims to discover the underlying structure of a set of observed variables. It is often used to reduce the dimensionality of data, identify latent factors, and test hypotheses about the relationships among variables. EFA can also help to simplify data interpretation, improve measurement reliability, and validate scales or instruments. In this article, you will learn what EFA is, how it works, and how to perform it. You will also learn about the different types of factor analysis, the steps involved in conducting EFA, the criteria for choosing the number of factors, the methods of factor extraction and rotation, and how to interpret and report the results of EFA. By the end of this article, you will be able to apply EFA to your data and answer questions such as: What are the main factors that explain the variation in my data? How many factors should I retain for my analysis? How are the observed variables related to the extracted…