Statistical Modeling
Prerequisites
1
Simple Linear Regression
2
Multiple Linear Regression
3
Regression Diagnostics
4
Qualitative Variables
5
Transformations
5.1
Squared Terms in Regression Models
5.2
Elasticity
6
Weighted Least Squares
7
Correlated Errors
8
Collinear Data
9
Collinear Analysis
10
Variable Selection
11
Factor Analysis
11.1
Foundations
11.2
Estimation
11.2.1
Principal Component Method
11.2.2
Principal Factor Solution
11.2.3
Maximum Likelihood Estimation
11.3
Rotation
11.4
Basic Factor Analysis in R
11.4.1
Data Preparation and Description
11.4.2
Selecting numbers of Factors
11.4.3
Applying Factor Analysis
11.4.4
Interpreting the Factors
Exercises
Appendix
Assignments
Presentation
Dataset
Seminar Paper
Examples
System Info
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Statistical Modeling
Chapter 10
Variable Selection
Figure 10.1:
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