I just gave up on another video, called “Multilinearity explained simply.” The second he started talking , i knew it wasn’t going to be simple. Then he talked more and I was done. Found this. The second YOU started talking , i knew it was going to be simple. And by the 21 second mark i had already caught on. Thanks for this. Just goes to show, titles mean nothing. This was explained well.
Man, this is absolute gold. I've been binge watching your videos for a few hours now and you've taught me more than my professor ever could in a whole semester! Thank you SO much.
You are phenomenal. I have studied statistics for many years and you are making me aware of things I never thought about. Thanks so much. Can you do a video on covariance???? Please
I'm in a class and not understanding the way they are trying to teach me these concept. I really appreciate you work and the way you explain things. Not sure why I'm taking a $2,000 class when I can learn more for the price of a "like" on your videos.
did ANYONE ELSE notice the It's Always Sunny in Philadelphia reference at 16:21 ? Am I the first to appreciate the effort put into making our statistics lecture culturally relevant? Mr. Zedstatistics, well done.
Hi, im doing econometrics in my 3rd year of college, thank you for helping me. I have an end sem exam this Thursday and this video is helping me a lot! Wish me luck!
This guy is awesome! His explanation is not only so clear and easy to understand, but it as well creates an opportunity for the student to think ahead before he gets to the point. Wonderful!
this video explanation is very easy to understand especially the use of graphics to make it more interesting. it shows clearly the solution if there are issue and the detection of VIF and correlation
I never thought I'd stumble upon a statistics video with not only a Sufjan Stevens vinyl in the background but also with It's Always Sunny references, immediately subscribed.
This video is interresting because it explain more about multicollinearity where it occurs when the X variables are related to themselves. It show that it gives an effect to 1 variables and hold the other variables constant and ways to handle when the problems occurs using remedies
Just awesome. getting going now. bivariates are very data set to deal with. a good understanding of root analysis from the first principle is important.
I have watched a few of your videos. You and your videos are brilliant. It is rare to see complex concepts made easy in such a credible, easy, and authentic way. I am surprised, why the views of videos are not in millions. May be ... you are creating quality stuff - talking concepts !! Others are talking tools e.g. SPSS, AMOS, PLS etc! Concepts are the core, but most viewers seek an easy, quick fix. Hence video-watching. Imagine you are packaging concepts and tools together somehow (without discounting the awesome quality of content your create). I think your content will be killer! Nevertheless, keep doing great things. You rock!
These are bar none the Best resources on statistics. You gave me something that NO other source has been able to.. An INTUITION! Thank you for making such an impact to a stanger's life
This video helps me to understand the topic that is so complicated to me at first until I found this video. The explanation is simple yet easy to understand. Salam dari Malaysia.
This video is very useful for those that is not understand about multicollinearity like me. So, after watching this video, I clearly know the remedies in multicollinearity, the VIF and so on . thanks sir for this useful video. i really understand with your explanation.
This video is one of my favorite videos because the way of the explanation is gold. I like the way you use the graphic to explain the intuition, how to detect multicollinearity probs, and its remedies. This video is great overall.
Multicollinearity occur when the X variables are related, or two independent variables are collinear when they are correlated with each other. It can bring many effect such as variance(standard errors) are inflated. But, there are several solutions for the problem. Thank you so much for the beautiful video and your great explanation.
This is one of my favourite channel which I easily can understand it. Multicollinearity is when X variables are correlated with each others, also I can know to detect it. Thank you for the awesome video.
Thank you for going into the small details that are usually not explained well in schools. I appreciate your efforts. And I really enjoy your accent - charming. ;)
I really like how the video explain by using a good graphic to make sure the student and the other people understand what is multicollinearity. There has an explain the intuition, how to detect multicollinearity probs, and its remedies. I like it.
This video will be my favorite list for me to study about multicollinearity. It is occur when there are gwo variable are related. When it get high value, there is a problem and in this video it provide an explanation about the solution to fixed the problem.
This video is very helpful to me to get more understanding about Multicollinearity . The clear explanation with the graphic make me more understand in this topic.
From the video, I have learn what is intuition, how to detect problem in multicollinearity and also suggest method to solve the issues. Thank you sharing this video. It is very helpful.
It is nice explaination . It use the map so we can see all of the topic in the multicoillinearity . It also tell us all about it and it is very easy to absorb . It is because the explain is slow and smooth .
It great to watch this video as I really understand about multicollinearity and about solution are used when multicollinearity happen. thank you for this video.
From this video, it shows us a very details regarding multicollinearity. It makes me understand what is intuition, whats the m/c problem and how to solve this problem. There are also using a good example in explaining this concepts.
Thank you for explaining about the multicollinearity step by step from intuition to perfect multicollinearity. I dont understand about this topic before this but right after im done watching this, I can understand it.
great video thanks. the clearest and most accessible explanation of multicolinearity I've seen. I wasn't aware of VIF but came from a more intuitive idea that correlated predictors were problematic, and conducted PCA to remedy this. The context in this case was a predictive NN, and I didn't find that PCA provided anything useful. I've used it a couple of other times as well, with little success. Anyway, thank you for providing such a clear, well-presented explanation. All the best!
This was great. I've been teaching myself linear algebra over the past 6 months and it's cools to see a real world example of ill-conditioned matrices and, in the final example, of a coefficient matrix who's columns don't form a basis. The real world context really helps cement those more abstract concepts.
You are the best bro, hope you will make many more content of statistics, trust me bro what you thought me in 30 minutes my teacher couldn't thought me in last 6 month.
This a great video for multicollinearity . Absolutely, you explained well from the intuition until the part which is perfectly multicollinearity. Too many examples in this video make me slowly understand the model and how to manage if there is a problem. Thank you for sharing !
Multicollinearity occurs when the X variables are related to each other. Find the VIF using the 1/1-R^2 k from each regression. They are four options for remedies, do nothing, remove one of the correlated variables, combine the correlated variables or use partial least squares or principal component.
This video really help me to understand about multicollinearity. This video explain step by step which make it easy for me to undertand it. There are two detection which is correlation and vif. Thank you for the great explanation
Lol your law firm is Always Sunny in Philadelphia. Presumably specializing in bird law. not a crossover i was expecting. Awesome man I love your videos
Well structured explanation. Your video makes me understand clearly now on detection of multicollinearity and the solution if there's any issue based on the option given. Thank you for this video!!
THE best! You’re teaching style is simply enlightening! You so effortlessly command audiences’ attention from the very start till the end and leave them with a full picture in their minds in one go! Thank you!
Thanks to this video, your great explanation about Intuition, detection method, remedies, Justin's Simulation and Perfect multicollinearity make me more understand and clear about multicollinearity. Its really help me to get a solution if there any issue with my data.
Totally YES for this awesome explanation 😍 He is explaining every single subtopic regarding multicollinearity and now I understand and get more clear about this multicollinearity 👍🏻
Thank you Justin for this awesome video! You've really nailed the explanation and covered all the edges. It's really helped clear alot of doubts and now thanks to you I truly understand the concepts. Please keep up the good work!
Multicollinearity exist when X variable are related or two variables are collinear and correlated with each other. I love the way he explained it cause it is simple but yeshh the information are there
Thanks for the information regarding the Multicollinearity. You have the best, complete and understanding content. You should make more video on economic. 👍 What i have learned is the definition of Multicollinearity that is iv correlated with each other, the test, detention, remedies on solution, perfect Multicollinearity. Yeah. Thank you so much.