One of the oldest multivariate techniques, factor analysis is closely related to PCA and even confused by many for PCA. However, it serves a totally different purpose. Uncover hidden dimensions in your data.
Upon completion of this module, participants will know:
- The difference between Factor Analysis & Principal Component Analysis
- Why and when to use Factor Analysis
- The required data layout to run the analysis in software packages
- How to choose the options based on the data specifics
- How to interpret the software output
- How to report the results of the analysis
This module is aimed at people information on several variables and who wish understand the underlying their dimensions.
This course introduces the important ideas in statistics and data analysis. It assumes that participants either have no previous knowledge of statistics or that they have not used statistics for a long time.
- Introduction to Factor Analysis & Historical Note
- The Principle of Latent Variables
- The Extraction of Latent Variables (Factors)
- Statistical Methods for Factor Extraction
- Enhancing Factor Interpretability with Rotations
- Software Packages
- Typical Software Outputs
- Technical Issues
Recommended Duration: 1 day
Course materials :