Factor analysis helps to cut through the clutter when you have a lot of correlated variables to explain a single effect.  

This course will help you understand Factor analysis and it’s link to linear regression. See how Principal Components Analysis is a cookie cutter technique to solve factor extraction and how it relates to Machine learning . 

What's covered?

Principal Components Analysis 

• Understanding principal components
• Eigen values and Eigen vectors
• Eigenvalue decomposition
• Using principal components for dimensionality reduction and exploratory factor analysis. 

Implementing PCA in Excel, R and Python

• Apply PCA to explain the returns of a technology stock like Apple
• Find the principal components and use them to build a regression model