27.22 19.55 6.00 S 19.55 21.88 13.36 6.00 13.36 25.32 "hich of the following could be the new variable y, ? A. Y₁ = -0.56x₁ +0.06x2 -0.83x3 C. y₁ = 0.62x, +0.62x₂ +0.62x3 E. y₁=0.54x, -0.78x₂-0.32x3 G. y₁=0.56x, +0.06x2 -0.83x3 Dout% of the total variance in the data is explained by y₁. tound to the nearest tenth as needed.) B. y₁ = -0.54x, -0.78x₂ +0.32x3 OD. y₁=0.54x, -0.78x₂ +0.32x3 F. y₁=0.62x₁ +0.63x₂ +0.47x3 OH. y₁=0.62x₁ +0.63x₂ -0.47x3
27.22 19.55 6.00 S 19.55 21.88 13.36 6.00 13.36 25.32 "hich of the following could be the new variable y, ? A. Y₁ = -0.56x₁ +0.06x2 -0.83x3 C. y₁ = 0.62x, +0.62x₂ +0.62x3 E. y₁=0.54x, -0.78x₂-0.32x3 G. y₁=0.56x, +0.06x2 -0.83x3 Dout% of the total variance in the data is explained by y₁. tound to the nearest tenth as needed.) B. y₁ = -0.54x, -0.78x₂ +0.32x3 OD. y₁=0.54x, -0.78x₂ +0.32x3 F. y₁=0.62x₁ +0.63x₂ +0.47x3 OH. y₁=0.62x₁ +0.63x₂ -0.47x3
Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018
18th Edition
ISBN:9780079039897
Author:Carter
Publisher:Carter
Chapter4: Equations Of Linear Functions
Section4.5: Correlation And Causation
Problem 11PPS
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![The covariance matrix of an image with three spectral components is shown below. Let x₁, x₂, and x denote the spectral components of each pixel in the image. Find a new variable of the form y₁ = C₁x₁ + ₂x₂ + 3x3 that has maximum
possible variance, subject to the constraint that c+c+c=1. What percentage of the total variance in the data is explained by y₁?
27.22 19.55 6.00
S= 19.55 21.88 13.36
6.00 13.36 25.32
Which of the following could be the new variable y, ?
OA. Y₁ = -0.56x₁ +0.06x₂ -0.83x3
OB. y₁ = -0.54x₁ -0.78x2 +0.32x3
OC. y₁ = 0.62x, +0.62x₂ +0.62x3
OD. y₁=0.54x₁ -0.78x2 +0.32%
E
O E. y₁ = 0.54x, -0.78x2 -0.32%
y₁ = 0.62x₁ +0.63x2 +0.47x3
OG. y₁=0.56x₁ +0.06x2 -0.83xg
OH. y₁=0.62x₁ +0.63x₂ -0.47x3
About % of the total variance in the data is explained by y₁
(Round to the nearest tenth as needed.)](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F619b53e8-d17b-4056-b8c7-65add7f2bd1d%2Fdc887aee-b49e-4603-b3a8-c3ab58c26094%2F0k4czfc_processed.png&w=3840&q=75)
Transcribed Image Text:The covariance matrix of an image with three spectral components is shown below. Let x₁, x₂, and x denote the spectral components of each pixel in the image. Find a new variable of the form y₁ = C₁x₁ + ₂x₂ + 3x3 that has maximum
possible variance, subject to the constraint that c+c+c=1. What percentage of the total variance in the data is explained by y₁?
27.22 19.55 6.00
S= 19.55 21.88 13.36
6.00 13.36 25.32
Which of the following could be the new variable y, ?
OA. Y₁ = -0.56x₁ +0.06x₂ -0.83x3
OB. y₁ = -0.54x₁ -0.78x2 +0.32x3
OC. y₁ = 0.62x, +0.62x₂ +0.62x3
OD. y₁=0.54x₁ -0.78x2 +0.32%
E
O E. y₁ = 0.54x, -0.78x2 -0.32%
y₁ = 0.62x₁ +0.63x2 +0.47x3
OG. y₁=0.56x₁ +0.06x2 -0.83xg
OH. y₁=0.62x₁ +0.63x₂ -0.47x3
About % of the total variance in the data is explained by y₁
(Round to the nearest tenth as needed.)
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