Principal Component Analysis - PCA (with detailed explanation)

Описание: The Video Timeline:
0.0 - 05:17 Synopsis (Introduction)
05:18 - 13:19 PCA Analysis Demonstrations
13:20 - 24:47 Results and Interpretations
24:48 - 25:19 Closing Remarks

In this video, I demonstrated how to perform Principal Component Analysis, giving a detailed explanation to every feature of the analysis. The application of principal Component Analysis has to do with the reduction of dimension of variables in a dataset, and in this video, I gave detailed description of the PCA, and listed the possible assumptions that a dataset must satisfy for the data to be tenable for the analysis.

After you have seen this video, you should be able to perform PCA and interpret KMO and Bartlett’s Test of Sphericity for sampling adequacy.

The content of this video is detailed and comprehensive, and the demonstration has been simplified to the grassroots.
So, you are hereby advised to see or watch this video to the end. Please, kindly share the link of this video for others to see and also benefit.

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