Connect the Dots: Factor Analysis

Factor extraction using PCA in Excel, R and Python

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


Using discussion forums

Please use the discussion forums on this course to engage with other students and to help each other out. Unfortunately, much as we would like to, it is not possible for us at Loonycorn to respond to individual questions from students:-(

We're super small and self-funded with only 2-3 people developing technical video content. Our mission is to make high-quality courses available at super low prices.

The only way to keep our prices this low is to *NOT offer additional technical support over email or in-person*. The truth is, direct support is hugely expensive and just does not scale.

We understand that this is not ideal and that a lot of students might benefit from this additional support. Hiring resources for additional support would make our offering much more expensive, thus defeating our original purpose.

It is a hard trade-off.

Thank you for your patience and understanding!