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You have 3 points (1, 6), (2, 4), and (4, 3). Find the best function to fit these data from the following functions: (1) y = a₁ + a₁x (2) y = AeBx (3) y = A + B ² Hint: 1-Data Linearization Method V = a₁ + a₂U k Σ=1ui rk k [Σ14: _Σημε[@] = Σ=10; k ¹2i=1 U₁ V₁]

You have 3 points (1, 6), (2, 4), and (4, 3). Find the best function to fit these data from the following functions: (1) y = a₁ + a₁x (2) y = AeBx (3) y = A + B ² Hint: 1-Data Linearization Method V = a₁ + a₂U k Σ=1ui rk k [Σ14: _Σημε[@] = Σ=10; k ¹2i=1 U₁ V₁]

Advanced Engineering Mathematics
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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Curve Fitting

You have 3 points (1, 6), (2, 4), and (4, 3). Find the best function to fit these data from the following functions: (1) y = a₁ + a₁x (2) y = Ae Bx (3) y = A + B ¹² Hint: 1-Data Linearization Method V = a₁ + a₁U Σ=10i [Σk ² = 1 Ui vi] Root mean-square error function Root mean-square error function e(f) is defined by: € (ƒ) = [ Σ*²=₁[Y(x^,) — y₁]²] ¹/² Σ=1ui k k [ Σ ² = ₁ U₂₁ [²²_₁ U ₁ ² ] [] B. Power Fit Method a = = Li=1 Σ1 xi¹¹ yi Σ=1x;2n
Transcribed Image Text:You have 3 points (1, 6), (2, 4), and (4, 3). Find the best function to fit these data from the following functions: (1) y = a₁ + a₁x (2) y = Ae Bx (3) y = A + B ¹² Hint: 1-Data Linearization Method V = a₁ + a₁U Σ=10i [Σk ² = 1 Ui vi] Root mean-square error function Root mean-square error function e(f) is defined by: € (ƒ) = [ Σ*²=₁[Y(x^,) — y₁]²] ¹/² Σ=1ui k k [ Σ ² = ₁ U₂₁ [²²_₁ U ₁ ² ] [] B. Power Fit Method a = = Li=1 Σ1 xi¹¹ yi Σ=1x;2n
Expert Solution
Step 1: Analysis and Information

Given points:

open parentheses 1 comma 6 close parentheses comma space open parentheses 2 comma 4 close parentheses comma space open parentheses 4 comma 3 close parentheses

Given functions:

1) y equals a subscript 0 plus a subscript 1 x

2) y equals A e to the power of B x end exponent

3) y equals A plus B over x

To find:

The function which is best fit on each models.

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