Connect the Dots: Factor Analysis




Connect the Dots: Factor Analysis

 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 

Factor extraction using PCA in Excel, R and Python

Url: View Details

What you will learn
  • Use Principal Components Analysis to Extract Factors
  • Build Regression Models with Principal Components in Excel, R, Python

Rating: 3.75

Level: All Levels

Duration: 1.5 hours

Instructor: Loony Corn


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