Factor analysis is a data analysis procedure that aims at extracting a small number of factors from a large number of items, that is, from variables. The extracted few factors should be able to describe and explain the core characteristics of a phenomenon, without the loss of too much information. Hence, factors show the essence
In statistics and econometrics, heterogeneity typically refers to a random variable, parameter, or distribution that varies across a population of interest. It can involve the mean, variance, or other features of a distribution and may arise from observed and unobserved causes. Observed heterogeneity is variability in an outcome (or dependent variable) attributable to observed predictors
Factor analysis is a statistical procedure for describing the interrelationships among a number of observed variables. Factor analysis is used to measure variables that cannot be measured directly, to summarize large amounts of data, and to develop and test theories. There are two broad categories of factor analysis: exploratory and confirmatory. Exploratory factor analysis techniques