The least squares error of a candidate measures how well that candidate line fits the data: E(m) = (yı – mx1)² + (y2 – mx2)² + .… ·+ (y7 – mx7)2 %3D Each term in the sum above represents the square of the distance between an actual data point Y; and the y-value of the candidate line at at x;. Why is this error a function of m?

Elementary Linear Algebra (MindTap Course List)
8th Edition
ISBN:9781305658004
Author:Ron Larson
Publisher:Ron Larson
Chapter5: Inner Product Spaces
Section5.CR: Review Exercises
Problem 62CR
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If I have a list of data and use the least squares error, why would the function be a function of m
The least squares error of a candidate measures how well that candidate
line fits the data:
E(m) = (yı – mx1)² + (y2 – mx2)² +...
+ (y7 – mx7)²
Each term in the sum above represents the square of the distance between an actual
data point Y; and the y-value of the candidate line at at x;. Why is this error a
function of m?
Transcribed Image Text:The least squares error of a candidate measures how well that candidate line fits the data: E(m) = (yı – mx1)² + (y2 – mx2)² +... + (y7 – mx7)² Each term in the sum above represents the square of the distance between an actual data point Y; and the y-value of the candidate line at at x;. Why is this error a function of m?
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