Exploratory Factor Analysis

Exploratory factor analysis (EFA) is a method that aims to uncover structures in large variable sets. If you have a data set with many variables, it is possible that some of them are interrelated, i.e. correlate with each other. These correlations are the basis of factor analysis.

The aim of the factor analysis is to divide the variables into groups. The aim is to separate those variables that correlate highly from those that correlate less strongly.

In Statistics Exploratory Factor Analysis is also called Principal Component Analysis (PCA)

More Information about Exploratory Factor Analysis

Here you can find the Factor Analysis Calculator

And the Data:

[ranthony]

I learn all this in 15 minutes what has taken 4 years and $10, 000. Thanks for this. Simple, clear with no distracting loud music.

[emilyjanesGS]

Varimax is an orthogonal rotation, which assumes that factors are unrelated to each other. In your example, you've used personality traits, which are psychological constructs and would be expected to be related to each other (in psych, constructs are rarely if ever completely unrelated). An oblique rotation, which assumes factors are related, would normally be the most sensible choice in psychology research. The appropriateness of orthogonal vs oblique rotation for their variables/discipline is something people should be aware of and consider in EFA.

[sarrakharbach]

WOW! I am so happy I found this channel!! So easy to follow, no distractions, no music, no extra visualizations. Just on point! Well done!

[shifatrimpu]

I was struggling with factor analysis and I had zero background in this. You video just saved my life, explained so nicely and such a clear visual representation within such short amount of time! Can't thank you more. Keep posting more please.

[naoremanand]

I have spent four years in learning these kind of courses and i found you. You are a life saver. Pls keep it up

[ivaniasobral]

You've done what my teacher couldn't, thank you

[innyn]

This is so simple, straightforward, and helpful. Thanks a lot!

[mtk]

Thank you so much. You provided a much clearer explanation that my lecturer or any text books!

[behailumulatie]

Lack words to appreciate your exemplary lecture!

[WenqiangYin]

Oh my god, you explain it so clear and none of my professors can explain it in such a clear, understandable way! YOU SAVED MY LIFE AND TIME! this is so Otherwise, I will need to spend more time in softwares

[shreyanshswarnakar]

One of the best lectures on EFA I have sat through

[NKushairi]

this is super duper easy to understand. God blessed. thank you very much!!! keep on sharing.

[baconandphil]

Great video! Great Explanations. This made me try the one month subscription to conduct an exploratory factor analysis. The software is easy to use and accessible immediately after purchase.
I can highly recommend it! Facilitated my research A LOT!

[percent-]

This is the perfect refresher video to help me remember what i learned years ago in class to prepare for my comprehensive exams. Thank you for this video

[davlukabb]

Thank you, this has been so helpful to me. I'm a 1st year PhD student in social sciences working on my first literature review.

[lisayip]

Easy and clear. Above my expection, very helpful. Thank you.

[MrJoesouth]

Why was I able to understand all of this, this was so understandable, thanks!

[kanchandatta]

I understood the concept communalities after listening your explanation. Thank you so much.

[swagata]

Really great. I have just started following all videos after watching this.

[MutianTait-om]

Loved your explanation! So easy to understand!