Connect the Dots: Factor Analysis | EdisonX Academy

Connect the Dots: Factor Analysis

Factor extraction using PCA in Excel, R and Python


  • Self-Paced $ 50 $ 12.5 3 weeks
    1-2 hours / week


  • No statistics background required. Everything is built up from basic math
  • The models are implemented in Excel, R and Python. Install these environments to follow along with the demos

About Course

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 


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