Principal component analysis

Discover how Principal Component Analysis can help you uncover hidden patterns and relationships in your data. Find out how to apply this powerful statistical technique to gain valuable insights.
The Fundamental Difference Between Principal Component Analysis and Factor Analysis Reading, Principal Component Analysis, Factors, Data Science Statistics, Data Analysis, Data Science, Control, Research Methods, Statistics Notes

Principal Component Analysis and Factor Analysis are similar in many ways. They appear to be varieties of the same analysis rather than two different methods. Yet there is a fundamental difference between them that has huge effects on how to use them.

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Principal Component Methods in R: Practical Guide - Articles - STHDA Data Analysis, Principal Component Analysis, Data Science Statistics, Data Table, Data Science, Data Visualization, Data, Algorithm

Principal component methods are used to summarize and visualize the information contained in a large multivariate data sets. Here, we provide practical examples and course videos to compute and interpret principal component methods (PCA, CA, MCA, MFA, etc) using R software. The following figure illustrates the type of analysis to be performed depending on the type of variables contained in the data set. The Book: Practical Guide to Principal Component Methods in R…

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Ian Kruger