Factor Analysis - an introduction
Вставка
- Опубліковано 19 лют 2014
- This video provides an introduction to factor analysis, and explains why this technique is often used in the social sciences. Check out ben-lambert.com/econometrics-... for course materials, and information regarding updates on each of the courses. Quite excitingly (for me at least), I am about to publish a whole series of new videos on Bayesian statistics on youtube. See here for information: ben-lambert.com/bayesian/ Accompanying this series, there will be a book: www.amazon.co.uk/gp/product/1...
It's 12:30 AM. The kids are in bed and I just did some reading, trying to wrap my head around the reasons (advantages and uses of factor analysis). This video was easier to understand than the reading and well-explained enough that I didn't fall asleep despite the hour. Kudos to you! On to part 2 as a result!
Thanks, Ben for this incredibly valuable series! The explanations and examples in these videos are so clear. I'm adding your book to my birthday wish list--you are an OUTSTANDING teacher!!!
This is by far the best introductory video to factor analysis. Thank you!
currently taking a module in uni that was teaching factor analysis and i never understood it until i chanced upon this video! such a coherent explanation illustrated with an intuitive example! thank you so much!
I am writing my finance thesis which requires the statistical method to test certain strategies. And This video helps me a lot for continuing constructing my finance strategy and testing its performance.
Great job Ben!
My teacher tried to explain the same thing in a 1.5 hour long class, you did better in just 8 minutes. Thanks!
some of these videos are more helpful than my unit provided lectures.. appreciated
Thank you Ben. I am so grateful to you because of the excellent material that you have explained so well ..
Just saved me from going crazy, makes sense now! Thanks
cheers mate, fantastic video. It cleared up some misconceptions I had from the book. Very much appreciated!
So well explained! Loving your channel Ben.
Thank you! These explanations helped a ton with my first year stats papers.
Thank you Professor. It is great revision. You made it simple and effective.
Thank you! This is helpful. I think I will watch it one more time to understand it better (all of this information is new to me).
Fabulous lesson. I'm currently in a Tests and Measures master's class. We need to do an assessment review of the Big Five, which as you know analyzes data using the statistical procedure of factor analysis; something not yet covered by my class. It doesn't help our professor doesn't lecture. We are made to read the book and loads of research, but we are left to extrapolate meaning. This is one class I regret taking online during COVID. Thank you for the clarification.
REALLY well explained .Thank you very much!
Thank you! Great learning material
Very clearly explained, thanks.
Ohhh… just been slogging through Manly textbook chapter on Factor Analysis, while also watching a great deal of this series, and getting more & more confused, until the chapter’s conclusion defined a few terms that really were needed at the start. Turns out this youtube series is mostly pertinent to CONFIRMATORY Factor Analysis, whereas Manly (& my upcoming assignment) is focussing on EXPLORATORY Factor Analysis. Which is … kinda different, back to front. Thankyou though! Things are definitely more clearly explained than the Manly textbook or my lecturer.
Very clear explanation. Thank you!
Thank you for sharing this!
Well Explained !! Thank you !!
Well explained and helpful video, nice one !
Thanks for the wonderful lecture in EFA.
I have a question:
The assumption that the measurement errors are not correlated with the factors and not correlated between them, this assumption isn't valid in reality?
Great video. Could you share (does anyone in the comments know) what presentation software is being used?
Very helpful. Thank you!
Excellent explanation
Thank you! It helped me a lot
Thanks a lot. Great video.
In the case of time series, do the series have to be stationary? Is there an assumption in factor analysis that requires this?
Thank you mate!
Hi, may I know what your specific source was for this lecture? :)
can you increase the volume?
Hi Ben,
Sorry I am very new to statistics so please ignore the foolishness of this question -
If you were to somehow cross analyse 'depression' and 'anxiety' (the underlying factors) against, say, age brackets what model of analysis would you suggest?
For example, if I divided the sample population into age brackets (0-14 years, 15-24 years, 25-54 years, 55-64 years, 65 years and over) and then wanted to show the prevalence of 'underlying factor X' and 'underlying factor Y' within each age bracket what model or method should I use to display this association?
Thanks so much!
Steven Norman I'd recommend checking out multi group confirmatory factor analysis, might be a good option
Best as usual.
Nice one, Ben :)
can i draw factor score on map?
So low sound intensity on such a great video made me uncomfort my self and get my headphones man... This is inhuman. Great video by the way!!!
thank you!!
Thanks a lot!
Wish the video was louder. Plus, if you could do some calculation examples maybe?
Captain, we need to reduce the dimensionality in order to increase the predictive power of the model!
It really helps! thx
Well explained thanks, but:
What do you mean by "unobserved" variables (depression and anxiety)? If they're unobserved that would mean (I assume) that they're not measured, in which case how would they be factored in?
When you start the analysis you dont have the names of your future factors but you have some data you are doing analysis on so i guess you would based on the resaults name the person prone to suicid and insomnia in a factor of depression. I am not 100% sure if that is correct but thats what i think the point is
Maybe think of it as clumping factors which are related into one factor somehow.
Unobserved variables are non-measurable concepts, that even likert scale needs multiple variables to understand... do you get my drift?
You've labelled the hidden factors as depression and anxiety but it's really just 2 factors that explain, right? ie dimensionalty reduction but who's to say what the factors really are?
Quiet video put sound on it.
Random question.. did you like real analysis?
it totally looks like a neural network.
talking about suicidal thoughts during an exam period is dangerous... good video tho
Whoosh
your presentation is excellent but you need to buy a mic because the voice is to low even maximum 100 value
Factory analysis: factor analysis on a humongous scale.
This video is way too quiet, I can't watch it.
With headphones the volume is good. Otherwise, it is pretty quiet.
This sounds remarkably like contemporary machine learning techniques.
audio not a factor
just what the fuck is he talkin about
got lost
Audio sucks
VAIR-EE-ABLES. FFS. How can anyone learn from someone who pronounces this word VAIR-ABLES?
You sound like someone, who had a very bad day. Hope you feel better now.
Chill the fuck out bitch. This guy took time out of his day to explain this shit.
Thank you for this! 🥹
it totally looks like a neural network.