3. Create another function for a linear regression. Pass to the function two arrays of data, the mean of the y data, and their length. You should pass out of your function m and b. 4. In this new function, using a for loop calculate the various sums needed to calculate m and b for the linear regression. 5. Calculate m and b. m = n n nΣ xq Vi X; Σ V₁ n i=1 i=1 i=1 n n 72 b=1=1 i=1 (x₂) ² n Σy₁-mΣx₁ n n i=1 n X ₁ 2

Database System Concepts
7th Edition
ISBN:9780078022159
Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Chapter1: Introduction
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3. Create another function for a linear regression. Pass to the function two arrays of data,
the mean of the y data, and their length. You should pass out of your function m and b.
In this new function, using a for loop calculate the various sums needed to calculate m
and b for the linear regression.
4.
5. Calculate m and b.
m =
n ¸X ₁ Vi
i=1
n
n
n
b = 1=1
n
i=1
(x₂) ²
Y ₁ - m
n
n
n
i=1
i=1
X;
n
X ₁
i=1
n
Σ.x₂
i=1
Vi
2
Transcribed Image Text:3. Create another function for a linear regression. Pass to the function two arrays of data, the mean of the y data, and their length. You should pass out of your function m and b. In this new function, using a for loop calculate the various sums needed to calculate m and b for the linear regression. 4. 5. Calculate m and b. m = n ¸X ₁ Vi i=1 n n n b = 1=1 n i=1 (x₂) ² Y ₁ - m n n n i=1 i=1 X; n X ₁ i=1 n Σ.x₂ i=1 Vi 2
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