Regression: Crash Course Statistics #32
Вставка
- Опубліковано 8 лют 2025
- Today we're going to introduce one of the most flexible statistical tools - the General Linear Model (or GLM). GLMs allow us to create many different models to help describe the world - you see them a lot in science, economics, and politics. Today we're going to build a hypothetical model to look at the relationship between likes and comments on a trending UA-cam video using the Regression Model. We'll be introducing other popular models over the next few episodes.
Crash Course is on Patreon! You can support us directly by signing up at / crashcourse
Thanks to the following Patrons for their generous monthly contributions that help keep Crash Course free for everyone forever:
Mark Brouwer, Kenneth F Penttinen, Trevin Beattie, Satya Ridhima Parvathaneni, Erika & Alexa Saur, Glenn Elliott, Justin Zingsheim, Jessica Wode, Eric Prestemon, Kathrin Benoit, Tom Trval, Jason Saslow, Nathan Taylor, Brian Thomas Gossett, Khaled El Shalakany, Indika Siriwardena, SR Foxley, Sam Ferguson, Yasenia Cruz, Eric Koslow, Caleb Weeks, D.A. Noe, Shawn Arnold, Malcolm Callis, Advait Shinde, William McGraw, Andrei Krishkevich, Rachel Bright, Mayumi Maeda, Kathy & Tim Philip, Jirat, Ian Dundore
--
Want to find Crash Course elsewhere on the internet?
Facebook - / youtubecrashcourse
Twitter - / thecrashcourse
Tumblr - / thecrashcourse
Support Crash Course on Patreon: / crashcourse
CC Kids: / crashcoursekids
This series is amazing! I have majored in Statistics and still this series explains everything much better than college classes.
You majored in statistics? Wow, and here I thought that I hated myself.
I swear this series is the reason I am actually doing well in statistics! Wish I had this in my BSC (MSc Student)
I think you guys are the reason people study or stay in school. net positive for humanity. thanks for helping people.
These graphical presentations are so good, especially at 8:30 the didferent sums of square types
BRAIN HURT!!!
nah actually I find it very fun, Z test T test F test and anova all has to do with std and variance which has to do with the mean
@@MasterofPlay7 I also LOVE stats. And this from a person that sold my math text books for toffee at school! Once you get it, it's so much fun!
@@nikkid4890 yes we human are too dumb, most statistical analysis have to do with a straight line (most models are based on y=ax+b) cuz we can only perceive the relationship through a straight line
Only crash course can make statistics interesting. Thank you for making quality educational videos for free! :D
the best thing about the video is how the pumpkin and the transformer slowly eat all the candy worms that were on the table during the video
Noru mosko ra pandhi!
Thanks
This course is sooo good. I'm using the Covid-19 Quaratine to educate myself in Statistics and this Crash Course was THE finding. Thanks a lot!
Good luck with Statistics!
This right here is the most entertaining and intriguing statistical video Ive ever watched.. it actually made stats fun, thanks for incorporating art and creativity to this piece ,,instead of old and boring numbers presented in a monotonic go to sleep now voice
This is great, especially the explaination of degrees of freedom. I never really understood it through five years of Economics so thank you.
This video is absolutely helpful! One single video and I understand the contents from 2 hours class.
This series is pointless... until you actually need this stuff for class and then you're thankful to God that it exists. Thanks for everything y'all do!
It was a very comprehensive, concise and crisp presentation on a complex topic. Kudos to the entire team for an excellent effort.
First minute and a half and i've actually learnt so much
Thank god for crash course lol, godsend channel to start to learn a topic when I gotta teach my brother about a topic I’ve never learned myself
every night brings a dream but the day, relentlessly, keeps me awakeee
Wow! You are brilliant. I'm post-grad and needed to refresh. Brilliant
Linear Regression is the building block in Artificial Intelligence predictions
Some unnecessarily confusing parts:
It would have been helpful to explain that our zero-coefficient line IS the line y='y hat'.
The point referred to at 7:05 is not highlighted or pointed out (and as it sits far above its distance for SSR it isn't instantly recognizable as connected).
Positioning of the equations at 8:50 gives strong and erroneous implication that each refers specifically to the diagram above.
The equation given for F-statistic at 8:58 is then instantly revised as not being correct.
The correct f-statistic equation is only on screen at 10:07 for a fraction of the time needed to read it - let alone fully digest it.
Exactly! I was so confused the whole time, a lot of it makes little sense if you see this stuff for the first time.
I think the F-statistic formulas are wrong at both 8:58 and 10:07 ! At 10:07 the denominator and numerator should be reversed!
Interesting. I just factchecked the theory about the comment-to-likes ratio, and it met pretty well: At the time I've written this, there were 41 comments and 391 likes, which is just the value "4000/100" shown in the diagram... As it turned out, this time it's above the regression line, but with an increase in the y-value by less than 35%
How can she keep speaking without inhaling!?
She is having a opera background I suppose.
Editing
@11:09
Editing ... they do it in all crash courses and other material
Rap God
She speaks a little too fast for me but clearly explained. I like it.
NOTE: This video uses the abbreviation "GLM" incorrectly (or at least very misleadingly) throughout.
The general linear model is NOT usually what is meant by "GLM". Instead, GLM stands for generaLIZED linear model, which is a special kind of linear model that (among other things) allows for a response variable that is not normally distributed. (Yes, this is extremely confusing. Don't even get me started on the word "linear", which doesn't even mean "straight lines" in this context.)
Bottom line: substitute simply "linear model" whenever Adrienne says "GLM" in this video, and you'll be fine.
Thank you this helped me so much! Will you do a video on multiple regression and econometrics in general? Keep up the good work you guys rock!
Did anyone notice how as the video goes on, there are less and less lollies (sweets) near the pumpkin lmao
It was a bit too fast, but very helpfull still! Will watch it a few more times.
So much clearer than my uni stats lecture!
So nice, can keep watching for hours.. Well done
You guys rock the house, super clear, super helpful!
this video is top production quality and expert instruction. thank you so much.
Who needs a regression calculation when you have "add trendline" in Excel?
who still uses excel in 2018 lol. keep up and learn python noob
The folks that want to work at Microsoft or any of it's competitors
Tntpker excel will forever be used, it has a great balance between learning curve and power. You must feel good about yourself putting strangers down over the internet.
I mean, that's what "add trendline" does. It does a regression on your data. :D
But a B-spline looks sooo much nicer!!!
Very interesting. One comment though. "The regression line is the one straight line that minimizes the sum of the squared distances of each point to the line" (3:50) can be slightly misleading. It seems to suggest the actual distance from each point to the line, which (except for a horizontal line) would not be vertical. It should say, "...minimizes the sum of the squared vertical distances from each point to the line."
This is Incredible
Well done! thanks so much for all the efforts! now i understand better!
So good! So helpful! Thank You!!
what a great explanation!! thank you so much!
Wow you opened my brains and I found it statistic is so fun!
One of the best episodes of the series. Mustaches - 9:22
So lost I want to cry, but seeing @AstroKatie was a nice pick me up
Thank you very much ❤
Insightful. Will read watch.
Easter egg alert: The candies dissapear while the video goes on :)
Amazing . Thanks for the info shot!
100/100 - great video
Bless you guys !
Can you go over nonlinear data models(exponential, power, etc) and also Simpson's paradox in the future?
I opened the CD cart, I haven't done that since Aprilish. I've regressed.
Great explanation
great video
good work ..it is really helping.
I really appreciate this explanation, but I think you started moving too quick when discussing degrees of freedom. I can't get what you're talking about after listening to it even several times. Specifically the lines she says at 19:13 are completely non-understandable to me. Thanks, though
19:13 doesnt exist
Ooo this is starting to get good...
You should have include nonlinear methods of regression in this video. Anyway, great video.
"I know Kung Fu" - Neo
"Show me." - Morpheus
For the trick or treat example, would it be appropriate to try a logarithmic transformation?
I Love this channel:) this is very helpful channel
Bless this video
We have to write a paragraph over what we learned from your videos every day in science class. I do it in 6th period.
Love your videos :D
AMAZING
At 9:33, she says 'The sums of squares for regression (SSR) has one degree of freedom as one degree is consumed in calculating slope of the model line'. How is that o.O
You mean it's all of us human being random number generators against UA-cams mechanical algorithms. "Of course you realize, this means war!"
Mam you are so sweet. thankx you teaching us.
I finally figured out the issue with this series, why it is so hard to follow. The animations are too much, too fast for statistics. I can barely follow through with the examples, or cannot follow at all. Example: the calculations; you can't remove each line before the next. I would want to see what numbers went where, and it is not that long of a calculation that you need to have space. Other than that, I think everything else is fine. Crash course Economics was awesome btw.
lmao i didn't understand anything
Math makes me cry
new video yay!
please add content of full machine learning algorithms
love it
Oh my , too fast for me🤯🤯🤯
At 9:43, do you mean “the mean”
In the null model, we are just using the mean of the data (one independent piece of info) to predict the outcome. You say “slope,” but aren’t we not using slope, i.e. setting it to zero?
It's at 9:34
"The sums of squares for regression (SSR) has one degree of freedom, because we are using one piece of independent information to estimate our coefficient, the slope"
Correct me if I'm wrong, but the sentence has to be "...we are using one piece of independent information to estimate SSR, the mean".
If this is incorrect, please explain why.
Didn’t really understand the degrees freedom part 🤔
*watches Optimus very closely throughout the video*
Thank you so much, this helped me a lot! :D
May i ask when the logistic regression video will be uploaded?
Can anyone recommend an exercise book or a site with practice questions for statistics? I feel like I need to practice it on my own. Cheers.
i don't understand why the sums of squares for regression has one degree of freedom
I DONT WANT TO OPEN TABACHNIK AND FIDELL
same, I don't get it
Because only 1 independent variable is used to generate the regression
I don't get why in 9:35 she says that we only need 1 degree of freedom to calculate the slop. I understand the 98 DF for SSE but I don't get why SSR has only 1 DF
I'm confused by the equation at 2:24. Should "increase in likes per comment" be in blue, standing for m instead of x?
Statistics are the ultimate rationalization of life's experiences through math. Unfortunately, the government and other organizations can take this oversimplification to back up their fallacies.
Only when their audience doesn't understand the stats. It's like small print in contracts (who reads those?) or those disclaimers in adverts in tiny print or really fast voices. Lessons like these help us to not be fooled.
This lady is a great presenter. I wish she was my teacher!
Useful video thanls. it looks like the alpha value used was 0.5. Should this be 0.05?
Did anyone else notice the bell curve in the background and where she sits positions her as being among the average? how funny is that! I’m not showing off my observational skills at all it’s just an observation.
Guess I'm the only one who noticed the gummy worms slowly disappearing...
best explaination ever!!!
If linear regression is for straight lines, how can regression be used to detect a curve? After all, how common a straight lines in science....
You can apply a transformation or use a different technique altogether, fully depends on what you are researching. As for straight lines in science, perfect lines, no, but approximations are enough. And those are abundant.
Baldur thank you.
The F-statistic formulas are wrong at both 8:58 and 10:07 ! Though the calculation is correct.
Just to F-up the F-Test, I'm gonna leave a comment without liking the video
Hi at 3:51 is it sum of(observed value minus predicted value)^2 or is it sum of(observed value minus average of values observed)^2
I remember statistics class in school was very challenging T_T
Said like a true psychologist
Well it seems easy when you get to watch entertaining, visually-stimulating videos and not have to be assessed for your application of the concepts with homework and exams...😂😂😂
@@DPMixing Yup, I am in AP stats with a 97% and watched this for fun to see how dumbed down it is. The answer: very.
How many more episodes will there be?
You can’t be like that glasses 👓 guy 🥺
This video is really helpful and the explanations are easy to understand. I think however some quiet music might be able to break the tension a bit, especially as the sound effects tend to get repetitive. Some quiet Lo-Fi instrumentals in the background could really help the videos seem even more polished.
Keep up the good work. ^^
I hope Crash Course helps me in college.
Im so lost
Next what? Correlation?
SIR PLZ MAKE VIDEOS ON MATHS IF U WANNA CROSS 10M COZ THERES MILLION OF SAME DEMAND
hi apitong 👋
I have notes I took pls love this I have watch ed you for so long
Motor Output: The response that occurs when your Nervous System activates certain parts of your body.
Key:
(MC)”word”: if its behind the word then it means it branches from it
“word”(MC):means is it’s the nervous system or (NS) that it may have branches.
Central Nervous System(CNS):
Brain and spinal cord.
Main control center.
Peripheral Nervous System(PNS):
All the nerves that branch off from the brain and spine that allow your CNS to communicate with the rest of your body.
Works in both directions (PNS)
Sensory Division(SD):
Picks up sensory stimuli.
Motor Division(MD):
Sends directions from your Brain to Muscles and Glands.
(MD)Sematic Nervous System(SNS): voluntary
rules skeletal muscle movement.
(MD)Autonomic Nervous System(ANS): involuntary
keeps your heart beating.
(ANS)Sympathetic Nervous System:
Mobilizes the body into action
(ANS)parasympathetic:
Relaxes the body
Astrocytes (Nervous System):
Exchanges materials between neurons and capillaries.
Microglial Cells(MC):
Immune defense against invading microorganisms.
(MC)Satellite Cells:
Surround and support Neuron cell bodies.
(MC)Schwan Cells:
Produce an insulating barrier called by Myelin Sheath.
Crazy facts about neurons:
1.They are the longest-lived cells in the human body.
2.They are irreplaceable.
3.They have huge appetites
please love/pin this :)I love your vids a lot especially the heart and lungs genres.
wtf lol?
what?
why youtube doesn't have heart button?