Factor Analysis is a technique that is used to reduce a large number of variables into fewer numbers of factors. It aims to find independent latent variables. It has several assumptions:
• There is a linear relationship
• There is no multicollinearity
• It includes relevant variables into the analysis
• There is a true correlation between variables and factors
There are different 4 types of methods used to extract the factor from the data set:
1.Principal Component Analysis
2. Common factor analysis
3. Image factoring
4. Maximum likelihood method