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

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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