Factor Analysis

 

Factor analysis is a statistical technique that reduces a set of variables by extracting all their commonalities into a smaller number of factors. It can also be called data reduction.

 

Factor analysis is a technique that is used to reduce a large number of variables into fewer numbers of factors.  This technique extracts maximum common variance from all variables and puts them into a common score. 

What is Factor Analysis? https://www.statisticshowto.com/factor-analysis/     Factor analysis is a powerful data reduction technique that enables researchers to investigate concepts that cannot easily be measured directly. By boiling down a large number of variables into a handful of comprehensible underlying factors, factor analysis results in easy-to-understand, actionable data.  Factor analysis is most commonly used to identify the relationship between all of the variables included in a given dataset.   The overall objective of factor analysis can be broken down into four smaller objectives:  To definitively understand how many factors are needed to explain common themes amongst a given set of variables. To determine the extent to which each variable in the dataset is associated with a common theme or factor. To provide an interpretation of the common factors in the dataset. To determine the degree to which each observed data point represents each theme or factor.