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Least square method
in regression line y = mx + b why m = this ¥¥ SumOf(x - Xbar)*(y - Ybar) m = ____________________________ SumOf(x - Xbar)² how this formula come ? and why this is equal to m ?
8 ответов
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edit:
Rajababu nicely explained here
https://www.mathsisfun.com/data/least-squares-regression.html
+ 6
I don't know but I think google can help you:
https://www.google.com/search?rlz=1C1AVNG_enBD832BD835&sxsrf=ALeKk03cpy3iZ6lCGOi3tVSSq0BsewtgcQ%3A1600528939006&ei=KiJmX4f6PMHEmAXApLygAw&q=how+does+least+squares+method+work&oq=how+does+least+squares+method+work&gs_lcp=CgZwc3ktYWIQAzIECAAQHjoECAAQRzoGCAAQBxAeOgYIABAIEB5QjEJY61RgkVloAHACeACAAb8DiAG1EJIBBzItNC4xLjKYAQCgAQGqAQdnd3Mtd2l6yAEIwAEB&sclient=psy-ab&ved=0ahUKEwiHt_L2wvXrAhVBIqYKHUASDzQQ4dUDCA0&uact=5
+ 4
yes m is the slope of the line but why that is equal to this formula ?
RKK
Mikhail
BroFar
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A J #Level 20
Atlas Hamington
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sir, anyone please help
+ 4
Coder Kitten how to take partial derivatives
+ 4
Coder Kitten message me
why df/dy = 2xy ?
+ 3
why the formula of m is this ?
BroFar
i have learned m = y2-y1/x2-x1
m = N Σ(xy) − Σx ΣyN Σ(x2) − (Σx)2
(N is the number of points.)
Intercept b:
b = Σy − m ΣxN
+ 3
You have some data points and want to find a regression curve that describes these set of points "adequately". So you need a method to get the parameters which summarize the data.
A least square method is one way getting the parameters. As the name says, it aims at minimizing square (deviation). However there are multiple least square methods. This is why you might encounter different formulas.