Let x₁, x₂ denote the variables for the two-dimensional data summarized by the covariance matrix, the eigenvalues, and the unit eigenvectors shown below. Find a new variable y, of the form y₁ = C₁ X₁ + ₂x₂, with c² + c²₂² = = 1, such that y, has maximum possible variance over the given data. How much of the variance in the data is explained by y₁? 31.6 16.6 -0.73 S= A₁ =47.121, u₁= 16,94₁ = [1 and λ₂ 13.847, U₂ = -0.68 -0.73 29.368 0.68 Y₁ = - 16.6 SCELE

Linear Algebra: A Modern Introduction
4th Edition
ISBN:9781285463247
Author:David Poole
Publisher:David Poole
Chapter3: Matrices
Section3.7: Applications
Problem 13EQ
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Let x₁, x₂ denote the variables for the two-dimensional data summarized by the covariance matrix, the eigenvalues, and the unit eigenvectors shown below. Find a new
variable y, of the form y₁ = C₁ X₁ + ₂x₂, with c² + c²₂² = = 1, such that y, has maximum possible variance over the given data. How much of the variance in the data is
explained by y₁?
-0.73
-0.68
S=
31.6 16.6
- 16.6 29.368
A₁ =47.121, u₁ =
14-[
and λ₂ 13.847, u₂ =
0.68
- 0.73
Y₁ =
Transcribed Image Text:Let x₁, x₂ denote the variables for the two-dimensional data summarized by the covariance matrix, the eigenvalues, and the unit eigenvectors shown below. Find a new variable y, of the form y₁ = C₁ X₁ + ₂x₂, with c² + c²₂² = = 1, such that y, has maximum possible variance over the given data. How much of the variance in the data is explained by y₁? -0.73 -0.68 S= 31.6 16.6 - 16.6 29.368 A₁ =47.121, u₁ = 14-[ and λ₂ 13.847, u₂ = 0.68 - 0.73 Y₁ =
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