Factor Analysis is a statistical technique that is useful for organizing and understanding datasets where there are high numbers of observed variables that are believed to reflect a smaller number of underlying variables. The research questions factor analysis can help you answer include:
How can we better understand and classify the variables in a dataset based on the observed interdependencies?
Based on the observed interdependencies, what variables in this data can be combined into a single factor? For example, can performance at running, ball throwing, batting, jumping, and weight lifting be combined into a single factor such as general athletic ability?
Based on the observed interdependencies, what are the most important variables in this dataset?
Based on the observed interdependencies, do survey items (or other measurement instruments) measure what they purport to measure?