In practice, Line of best fit or regression line is found when _____________(a) Sum of residuals (∑(Y – h(X))) is minimum(b) Sum of the absolute value of residuals (∑|Y-h(X)|) is maximum(c) Sum of the square of residuals ( ∑ (Y-h(X))2) is minimum(d) Sum of the square of residuals ( ∑ (Y-h(X))2) is maximumThis question was addressed to me during an internship interview.This question is from Linear Regression in section Commands, Packages, Visualizing Data and Linear Regression of R Programming

In practice, Line of best fit or regression line is found when _______

1.	In practice, Line of best fit or regression line is found when _____________(a) Sum of residuals (∑(Y – h(X))) is minimum(b) Sum of the absolute value of residuals (∑\|Y-h(X)\|) is maximum(c) Sum of the square of residuals ( ∑ (Y-h(X))2) is minimum(d) Sum of the square of residuals ( ∑ (Y-h(X))2) is maximumThis question was addressed to me during an internship interview.This question is from Linear Regression in section Commands, Packages, Visualizing Data and Linear Regression of R Programming
Answer» The CORRECT option is (C) Sum of the square of residuals ( ∑ (Y-h(X))2) is minimum The EXPLANATION is: Here we penalize higher error value much more as compared to the smaller one, such that there is a significant difference between MAKING big errors and small errors, which makes it EASY to differentiate and select the best fit line.

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