Part 2 101 1122. Having computed A from #1 above:I. Write down the equation of the best fit line (i.e. the estimation function), noting that the first entry of A is theintercept and the second, the slope.II. Compute Ŷ = FA, i.e. where the data point should have been to lie exactly on the line.3. Next, compute the least squared error E = ||Y – Ý|| ²/NOTE: All computations must be done by hand. Show detailed steps taken.1. Given that F=2Y:68.-compute A = (FT F)−¹ FTY.

Answered: 1 0 6- 1 1 1 2 2. Having computed A…

Advanced Engineering Mathematics

10th Edition

ISBN:9780470458365

Author:Erwin Kreyszig

Publisher:Erwin Kreyszig

Chapter2: Second-order Linear Odes

Section: Chapter Questions

Problem 1RQ

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Question

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Part 2

1
0
1 1
1
2
2. Having computed A from #1 above:
I. Write down the equation of the best fit line (i.e. the estimation function), noting that the first entry of A is the
intercept and the second, the slope.
II. Compute Ŷ = FA, i.e. where the data point should have been to lie exactly on the line.
3. Next, compute the least squared error E = ||Y – Ý|| ²/
NOTE: All computations must be done by hand. Show detailed steps taken.
1. Given that F
=
2
Y:
6
8.
-
compute A = (FT F)−¹ FTY.

Expert Solution

Step 1

Disclaimer: Since, you have asked to solve Q 2 only, only two parts Q 2 are solved. Please find the answer below.

What is Best Fit Line:

The least squares approach is used to find a regression line or best-fitted line for any set of data that is described by an equation. By lowering the sum of the squares of the residual sections of the points from the curve or line, this method allows for the quantitative discovery of the results' trend. The least squares method is used in regression analysis to determine the curve by fitting equations to the data.

Given:

Given,

$F = [\begin{matrix} 1 & 0 \\ 1 & 1 \\ 1 & 2 \end{matrix}], Y = [\begin{matrix} 6 \\ 0 \\ 0 \end{matrix}]$