What is Principal Component Analysis (PCA)?

[@sathasiva1885]

Wonder if the presenter a statistican or mathematican? She is a great teacher with clarity and not a word uttered in excess.

[@circuthead]

thanks for the explanation and the clarity while teaching

[@oreganorx7]

Very interesting. Just wanted to point out though that in the example you work through, when you look at the scatter plot for F1 and F2 you are not so much splitting the cars into big and small along the F1 axis, and powerful and not-powerful along the F2 axis as you are splitting them by power/weight ratio (F2 axis) and power.weight product (F1 axis).

[@Shabbir2749]

Kindly tell how can the line pointer can be chage to arrow🏹

[@danielcasasorozco2978]

Is it possible to link to the dataset? A very expainatory video, thanks a lot!

[@Midoritysha]

Thank you! just one question, how do you know that Factor1 is the size and factor 2 is the power??

[@VAIKHARIVADADKAR-RMRM]

great explanation, just one question about factor loading which factor loading to consider among 5 factors

[@XLSTAT]

Hello, It depends on the percentage of inertia explained. Usually, the two first factorial axes are taken but if they do not explain enough inertia you can take into consideration the third one as well and study the two first factorial planes. Best, Your XLSTAT Team

[@super007mat]

Merci! Please continue to create these tutorials

[@safaeaithamou2132]

où je peut trouver le document !?

[@raimondogramaglia]

thanks so much for this clear tutorial. i will use it for my thesis. God bless you XD

[@nashiehun9141]

How did the thesis go, kindly share the link I would love to know how you interpreted the data

[@KulbirAhluwalia]

Your voice is so soothing :)

[@PradeepSharma-qp7wf]

i have 5 cell reads...like c1,c2,c3,c4,c5 fr0m this c1 0ccupied 85% 0f variance.... s0 what is that means?

[@Tupol1]

How can I use PCA in Multivariate GARCH Models?

[@veniagl3984]

well done, excellent explanation!

[@Mike-uz9hs]

How do you know which sides represent size or power? This is really educational but i just dont get that part (14:00).

[@XLSTAT]

Hi! You need to interpret your observations graph with the correlation plot. The variables are represented on the correlation plot, where you can see if a variable is more correlated to the first, or the second component (or the 3rd, or the 4th ...)

[@Mike-uz9hs]

XLSTAT hey, thanks for the response. Yes I get you need to compare it to the red graph, but I dont understand how to tell which variables are represented by which quadrants? Is the top part speed because speed is the first arrow? Edit - sorry I meant power. Why do you read it as power and not speed?

[@engineerSalih]

Great explanation . Thank you.

[@Tupol1]

Ces´t incroyable! Tu es incroyable aussi. Can you use PCA in portfolio analysis?

[@alitahayaseen7350]

Thank you so much

[@bhagyaraju6626]

good explanation

[@sebastianquiroga1153]

Did you download any add-in on Excel? mine doesn´t have those options . Thanks in advance.

[@z0mb1e123321123]

+Sebastian Quiroga you should download XLSTAT to use this functions

[@tnrusri1897]

Is there anyway I can get the slides that you described?

[@XLSTAT]

Unfortunately, the slides are not available. We hope this tutorial will help you go further: help.xlstat.com/customer/en/portal/articles/2062222

[@tnrusri1897]

Thank you!!

[@sanaaelhatmi311]

so interesting thanks !

[@XLSTAT]

Thank you! You can discover our new Stat café videos too :) : kzbin.info/aero/PLwEkGOOAKKYZdzGGiEtk1bNnspN32zqoY

[@elsayedamr]

How can I get the link for the excel file to try it?

[@XLSTAT]

You can download the excel file here: help.xlstat.com/customer/portal/kb_article_attachments/109621/original.xlsx?1491232884

[@stevenkim4216]

I have a questions. What is a Factor(F)? And What does negative correlation mean in correlation matrix?

[@XLSTAT]

Hi! In PCA, a factor is an axis, or dimension. Factor(F) would be dimension number F. A negative correlation means there is a negative link between one variable and another, or between one variable and a PCA axis; Which means when one increases, the other decreases

[@DrRatishMishra]

I am going to perform same but unable to get sample and variable together in Biplot.

[@XLSTAT]

Hi! Can you send us an email at: [e-mail] with your data and analysis?

[@nikhilnambiar7160]

I have couple of questions. 1. Does every eigenvector form an principal axis? 2. How is largest axis is obtained? please do reply

[@XLSTAT]

Hi, 1. Yes! 2. Watch this video to see an animation of how the largest axis is obtained: kzbin.info/www/bejne/kJTHf5uIrdGFaJI

[@saniisahabba4023]

Pls how can i get this slide

[@XLSTAT]

Unfortunately, the slides are not available. We hope this tutorial will help you go further: help.xlstat.com/customer/en/portal/articles/2062222

[@jocarrero]

Great job, thanks

[@myouldash]

Brilliant!

[@maryamghadiri3474]

it was very helpful, thanks :)

[@saulgoodalvarez]

Incredible

[@XLSTAT]

A soft and easy "à la française" intro to Principal Component Analysis #datamining #statistics kzbin.info/www/bejne/nGrQi2uaiNeJgKM

[@farhanshams7286]

I really love your accent ... Are you French? :)

[@anjana4886]

thanks

[@mustafahussainmohsin320]

Awesome Explanation :) Thanks!!! and Nice Accent :P XD

[@AhmadAlQinneh]

brilliant

[@ehsanmorav]

good visualization

[@Aqlor]

She can be a computer scientist. This is used in pattern recognition, for example.

[@SarveshwarInani]

Thanks...

[@KhaledBadr28]

very helpful thanks (Y)

[@TheClarko1234]

@stav1472 sounds pretty French to me my friend. Dont hear this enough here in Scotland. ..so I just trawl you tube watching random videos in the hope ill hear another!

[@MrMadwyn]

feel the same

[@estershu]

French accent definitely!

[@jordim7902]

Could have been a great video If you had made conclusions out of the results observed. But you just mentioned what we already see. Still a useful video though!

[@Regimeshifts]

Agreed. Really enjoyed the video and at the end I was a bit disappointed because I think didnt get what everything meant. Great video though indeed!

[@imamanrana]

voice 😍

[@smartcat001]

Blurred visuals.

[@HamzaAbahri]

I can't focus because of her accent :'(

[@lilianagonzalezarciniega8475]

+Hamza Abahri hahahaha, her accent sounds so funny

[@naikgulzar]

nyc 1

[@artinmay2010]

-3 thank you!

[@felixg4785]

Definitely French!

[@Regimeshifts]

You don't say?

[@ronchu8669]

Guess you missed out on a pretty great tutorial

[@thepoo1234]

Happy face kind of looks like Patton Oswalt.

[@fj4eva69]

shoot me if i ever become a statistician

[@BiznatchWang]

god bless the french

[@TheClarko1234]

Stopped listening to the interpretation and began dreaming about that accent after 0:05....

[@iobdennis]

Terrible audio!

[@fararabemanolontsoa8628]

Awful french accent! shouldn't be on a scientific tutorial