#10 Principal Component Analysis: Theory in Excel with XLSTAT

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Principal component Analysis or PCA easily summarizes information from several quantitative variables.

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Stat Café - Question of the Day is a playlist aiming at explaining simple or complex statistical features with applications in Excel and XLSTAT based on real life examples.
Do not hesitate to share your questions in the comments. We will be happy to answer you.

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Produced by: Addinsoft
Directed by: Nicolas Lorenzi
Script by: Jean Paul Maalouf
  1. XLSTAT
  2. principal component analysis
  3. pca
  4. statistics
  5. excel
  6. xlstat
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Комментарии
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Very good formatting, background, music, info etc
Awesome vedio

manikgoel
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Excellent video - thanks. Do you know which version of XLSTAT is needed for performing PCA?

MS-yydh
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Great effort... I loved the setting. Trying to learn PCA... All the best with your future videos.

elvinthomas
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Hello, i have seen all your PCA video but can i ask a question? Did the factor score is the total of multiply the eigenvector and the observation data? Why when i'm search it say that the factor score is the total of multiply the eigenvector with the standardized obeservation data?? What is the difference between the observation data and the standardized observation data?? Please help me as i need to use it in my thesis🙏🙏

ninawina
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Does the data requires auto-scaling before using PCA?

If some variable have a much higher value, does it 'dominates' the results?

coldbrewed
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waa :( I need the nex video to finish my thesis jejje

sergitonx
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Hi, I've seen all your PCA videos and I have a question: I would like to know how to interpret the eigenvalue, what exactly does it mean? Please, I need the help for my thesis :(

Shadia_pm