Factor analysis is a statistical method used to analyze the relationships among a large number of variables and identify underlying factors that explain these relationships. It is often used in psychology, sociology, marketing, and other social science disciplines to reduce the complexity of data and identify patterns or underlying structures. Factor analysis works by identifying groups of variables that tend to vary together, known as factors, which are used to explain the variations in the data. These factors are typically unobservable and represent latent variables that are not directly measured but are inferred based on the patterns in the data. The ultimate goal of factor analysis is to reduce the complexity of the data and identify the underlying factors that can explain the relationships among the variables. This can help researchers better understand the underlying structure of their data, identify patterns or trends that may not be immediately apparent, and make informed decisions based on the relationships between variables.