Least Square Method (Curve Fitting)
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- Опубліковано 14 жов 2024
- Least square method or Least square regression is an approach followed in curve fitting, where we obtain the best-fit curve/line corresponding to a set of data points. This approach tries to minimize the sum of the square of the errors (or residuals) in the set of data points.
In this video, I try to obtain the slope and intercept of a best fit straight line passing through a set of data points using the Least square method.
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You are the best at explaining the linear regression on youtube! Kudos!
Key takeaway: To get the ideal/desired/expected straight line through the scattered dots (x-y plot), minimize the error values and keep the line as close to the dots as possible. Error values can be negative, so minimize the square of error values. Hence, the concept "Least Square Method".
Wow! This indeed is among the best explanations on LS method. Kudos to the teacher. Thanks.
Wow! Outstanding explanation. "For The Love Of Physics" is one of my most favorite UA-cam channel for a reason, and that reason flashes in front of my eyes everytime.
I am a pharmacy student, tried hard to find and learn this curve fitting but this video just solved all my hustle over browsing and understand little by little. Would say you explained it in the best possible way it could have been. Thankyou.
Great Explanation. Cleared all the doubts in one go. Loved it.
Awesome content delivered with such an ease.Hats off to you sir!
explained in an extremely concise manner! thank you very much sir :)
The best explanation of least square.
Wonderful!!!
Hey man, congratulations from Brazil! Very good material, I finally understand this method! Thank you so much!
Best explaition sir. You are great ,keep making such type videos and one day world's best scientist ,economist will become from india.
Best explanation . I'm satisfied.
Totally brilliant! You have a gift which is rare, i.e. the gift of teaching. Do you have a Patreon account? If you don't then you should get one.
Thanks bhaiya bohot achhe se samjhayan Hain aapne... Thanks a lott❤
Thanks Sir, unbelievably your video permanently fixed least square method in my mind.
Great way of explaining ---- I am impressed
thanks so much, infact i have understood this without having to cram the formulae.
sir, you make your thoughts as a tool in real problems explanation, that was nice and ever wonderful explanation on mathematics.
You're the best. So the errors are the residues?
amazing sir,
I am an Engineering Student from IIT Kanpur,
Mujhe jo teacher ne padhata the such me kuch samjh nhi aya but appse padhne ke baad,
I was like , Ye kya h
thank you sir 😊😊😊😊😊😊
Best explanation
Thank you so much for explaining
This is really awesome!
I am learning data science.
Plz do a tutorial on logistic regression
You have cleared my concept about least square method better than my professor who teaches us numerical analysis .
Sir namaskar... All lecturers are really very informative and interesting. It's my humble request to you kindly makes videos on time dependent Schrodingers equation. Thank you.
Perfect point to point clear explanation. I loved it.
Thank you very much sir, This video cleared my final doubts about curve fitting. Thank you very much sir. Heartfelt Love for you sir.
Thank you Sir, very nicely explained. Please make a video on non linear curve fitting also.
very good explanation
Realy asome explanation sir..
great video! Thanks
Sir, this video is very helpful n I always appreciate the way you present "the content" :D .
Loved your video great work
You're the best sir.
Nice explanation sir
Great explanation. Thanks, man.
Very informative, thank you
you are the best, thanks man!
wow sir very nice u explain this topic very beautifully
Well explained sir. Can you please let me know the Digital Tool or device you used for writing in this video?
Is there a playlist or another channel for enginnering maths
smooth understanding...Thanks
When I was watching this, I had a a question which was - how can just dy/dx confirm minima here(it could be maxima as well)? I thought about it, and it was because E = (yi-f(x))^2 is an upwards parabola, and double differential will always be positive, hence dy/dx=0 will be true only for a minima point. I left school over 10 years back, but I really enjoyed this video.
Can you please explain it a bit further ?
Plz make some other videos on numerical analysis topics..
Thank you so much sir 🌸
Now I have it in my head till eternity.
The main purpose is to find the f(x), which will minimize the Errors?
Even after I completed BSc(H) Physics from Hansraj you still teach me DJ sir!
Excellent explanation
Great video sir... 👍 Awesome explanation ❤
well explained
Great lecture! Keep up the good work.
this was a damm good explanation, thank you so much sir
Very good dibya....keep it up.
Brilliant ! Thank you
Superb sir
Thank you
awosome, my all doubts cleared......... how i can contact to you sir, need your help. i m new in this field.
Awesome!
Great, could you tell us what are the software and tools you used in writing and explaining please
very nice!
Good day sir. I wonder if i can ask for a video about (monte carlo simulation)? ?
Thank you yr ❤️❤️
4:30 why don't we take modules of all negative errors and then simply added by positive error, instead of squaring errors?
Sir, what's software did you use for this tutorial
Sir, can we plot count vs voltage characteristic of Geiger Muller counter using least square method.If yes it will be for straight line or for quadratic equation as we require equation for using least square method.
Wt type of technology use to explain this lecture,tell me Sir
Helpful video
Thanks for amazing video 👏🏼👍🏻
sir can we take difference f(xi)-yi for neglecting the negative values
Excellent explanation sir..can u provide pdf on this topic
Jabardast.👌
Happy teachers day ☺️ ☺️ ☺️
Thank you.. God bless 🙏
Thanku sooo.. M7ch sir...
I was just looking for this kind of explanation
which software u use for writing
Thanks
Perfect 😎
sir please tell how to draw a curve for Helmholtz Coil
So on line 9 of the code shown at about 14:20, where does that 5 in the matrix come from?
The element a22 of A will be n i.e. the number of datapoints we have.
Hence, here he considered 9 datapoints (as you can count in matrix A and B), so here the value of n = 9, hence a22 will be 9, but I think he wrote 5 there by mistake. It will be 9 there.
Sir, please give videos on relativistic quantum mechanics
helped me with ph110 xD
ty sir
A(2,2) should be '8', I think.
❤
The nuclear physics playlist??
I will upload that too.. soon
If there were not Indian guys nobody would have a chance to learn math
😂💔
Sir one humble request... when u taking class while standing with chalk only clear n we can understand.... while u sitting i feel u going fast fast fast... i personally feel that i couldn't understand sir... can u please stand n teach like before sir.. will u?
Thanks for the suggestion. I may have been a bit fast in this video anyways. I don't know how much sitting/standing has to do with it. I will try to work on your suggestion and see how it can be improved
@@FortheLoveofPhysics sorry sir if i hurted... am asking can u talk slowly because am from Tamilnadu n from childhood am tamil medium only so i have language problem also so that i asked u sir... i knew u r doing great job sir n its not easy also... u r covering the portion of TRB exam syllabus sir really great help sir first want to say thank u so much... if anything hurted u am really sorry sir... u please continue ur great work it will be helpful for more people sir....
Hi, its alright. No harm done. I m continually looking for feedback to improve my videos. So your suggestion is welcome. Don't worry about it :)
@@FortheLoveofPhysics Thank you for your polite words sir... keep rock...
@@FortheLoveofPhysics ❤
why do I need to use error squared? You just elevated the polinomial complexity to one degree higher by using squares! Negative error is not a reason to to convert it into a complex squared function, you could just calculated as the average of errors, using abs(error) and that's it. This method is too complex for this tiny problem!
its way more accurate than without squares
Sir can you please help me
How can we contact u sir email or insta🙏🙏🙏