Connect the Dots: Factor Analysis
Factor extraction using PCA in Excel, R and Python
Ratings 4.17 / 5.00
What You Will Learn!
- Use Principal Components Analysis to Extract Factors
- Build Regression Models with Principal Components in Excel, R, Python
Description
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
Who Should Attend!
- Yep! Data analysts who want to move from summarizing data to explaining and prediction
- Yep! Folks aspiring to be data scientists
- Yep! Any business professionals who want to apply Factor analysis and Linear regression to solve relevant problems
