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Connect the Dots: Factor Analysis in Excel, Python and R
Introduction
You, This Course and Us (1:45)
Factor Analysis and PCA
Factor Analysis and the Link to Regression (8:03)
Factor Analysis and PCA (7:00)
Basic Statistics Required for PCA
Mean and Variance (6:03)
Covariance and Covariance Matrices (11:45)
Covariance vs Correlation (3:19)
Diving into Principal Components Analysis
The Intuition Behind Principal Components (5:16)
Finding Principal Components (7:10)
Understanding the Results of PCA - Eigen Values (4:05)
Using Eigen Vectors to find Principal Components (2:31)
When not to use PCA (2:25)
PCA in Excel
Setting up the data (6:52)
Computing Correlation and Covariance Matrices (3:27)
PCA using Excel and VBA (5:51)
PCA and Regression (2:56)
PCA in R
Setting up the data (5:16)
PCA and Regression using Eigen Decomposition (3:58)
PCA in R using packages (1:56)
PCA in Python
PCA and Regression in Python (6:42)
PCA and Regression using Eigen Decomposition
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