Linear Regression: Example

Learn via an example how to regress data to a straight line. For more videos and resources on this topic, please visit nm.mathforcolle...

[@mayafelistiani3221]

It's really help.. May the God bless you..

[@JamesBedford]

Really great, clear example - thanks!

[@EjCab7]

thank you! youre a life saver! seriously. :)

[@numericalmethodsguy]

You should be watching the whole playlist to get a full understanding. This is the example part of the lesson. Go to numericalmethods(dot)eng(dot)u­sf(dot)edu, click on keyword, click on Linear Regression and watch and learn the videos in sequence. There is also a playlist at the channel if you directly want to see it on the youtube channel.

[@numericalmethodsguy]

Yes, that is called transforming data! Go to nm(dot)mathforcollege(dot)com and click on Keyword. Click on Nonlinear Regression. You will see videos on transforming data. See videos#3,4,5,10,11,12

[@aleatoriu5]

Very nice, man! Thanks!

[@chewy6i]

how was the formula for k2 derived? more insight would have been better for understanding.

[@tl425]

Hello Sir, I just wonder how can we solve this kind of question when it comes to second order equation like this: y = a0 + a1x+ a2(x^2)....

[@numericalmethodsguy]

Look at the last four videos here. nm.mathforcollege.com/topics/nonlinear_regression.html

[@alexandrecesar207]

Sir, what if i want to calculate the parameters of nonlinear equations like R = k*(Ca^a*Cb^b) supposing that i have data from R,Ca,Cb and my parameters are k, a and b?

[@numericalmethodsguy]

You can set up the sum of the squares of the residuals. Take derivative wrt k, a and b and set each one equal to zero. You will get 3 simultaneous nonlinear equations. You will need to solve them numerically to find k, a and b. You may be able to reduce 3 nonlinear equations to two in your case, but you still will need to solve them numerically.

[@alexandrecesar207]

thank you sir for the answer, i appreciate that very much!

[@TheChankaa]

thanks!

[@PatrickFeeneyguitar]

great!!

[@exkillerd]

5 stars. :3

[@physioflex]

guy knows good stats but no accent eh