FINISH the derivation (i.e. provide each of the remaining steps) to obtain these two formulas (in "Part b") for m and b from the two equations provided in "Part a." Consider this set of "w,z" data (there are "n" pairs of "w,z” data here):[W], W2, W3, ... ,[Z1, Z2, Z3,..., Ζη]The "best" linear fit parameters (i.e. Z¡ = m w¡ + b) are obtained from solving the following two equations:,Wh]Ηm Σw; + b n =j=1nΣτi=1nΠm Σ(w;3) + b Σwi -=i=li=1nΣ(w;z;)j=1 Part b)The following formulas provide the “best” linear fit (i.e. Z¡ = m w¡ + b) for this "w,z" data:m =b =nnnΣwi Ezi -n Σ(w; zi)1 {(W; 2₂)i=1i=1i=1nn( [w₁) ² - nΣ(w₁²)W;i=1i=1nnnnΣω; Σ(wizi) - Σ(w;2) Σεi=1i=1i = 1i=1กn({w;)² - nΣ(w₁²2)i=1i=1FINISH the derivation (i.e. provide each of the remaining steps) to obtain these two formulas form and b from the two equations provided in "Part a."

Given {w1, w2, ......wn}{z1,z2,.........zn } Zi=m wi+b

Consider this set of "w,z" data (there are "n" pairs of "w,z" data here): [W₁, W2, W3, [Z1, Z2, Z3,..., Zn] he "best" linear fit parameters (i.e. Z; = m w; + b) are obtained from solving the following two equations: wn]

Consider this set of "w,z" data (there are "n" pairs of "w,z" data here): [W₁, W2, W3, [Z1, Z2, Z3,..., Zn] he "best" linear fit parameters (i.e. Z; = m w; + b) are obtained from solving the following two equations: wn]

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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Question

FINISH the derivation (i.e. provide each of the remaining steps) to obtain these two formulas (in "Part b") for m and b from the two equations provided in "Part a."

Consider this set of "w,z" data (there are "n" pairs of "w,z” data here):
[W], W2, W3, ... ,
[Z1, Z2, Z3,..., Ζη]
The "best" linear fit parameters (i.e. Z¡ = m w¡ + b) are obtained from solving the following two equations:
,Wh]
Η
m Σw; + b n =
j=1
n
Στ
i=1
n
Π
m Σ(w;3) + b Σwi -
=
i=l
i=1
n
Σ(w;z;)
j=1

Part b)
The following formulas provide the “best” linear fit (i.e. Z¡ = m w¡ + b) for this "w,z" data:
m =
b =
n
n
n
Σwi Ezi -n Σ(w; zi)
1 {(W; 2₂)
i=1
i=1
i=1
n
n
( [w₁) ² - nΣ(w₁²)
W;
i=1
i=1
n
n
n
n
Σω; Σ(wizi) - Σ(w;2) Σε
i=1
i=1
i = 1
i=1
ก
n
({w;)² - nΣ(w₁²2)
i=1
i=1
FINISH the derivation (i.e. provide each of the remaining steps) to obtain these two formulas for
m and b from the two equations provided in "Part a."

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