There are 39 observations representing the 39 Peruvians in the dataset and 10 variables. Principal Component Analysis was performed on the data set, giving the following result based on the correlation matrix. Component eValue Total 1 3.449237 40.00% 2 1.692153 35.00% 3 1.543212 4 0.856276 5 0.783724 6 0.606369 7 0.438018 8 0.328671 9 0.205767 10 0.096575 10 30.00% 25.00% 20.00% 15.00% 10.00% 5.00% 0.00% 3 Scree Plot 4 5 6 9 10 Based on the "detect the elbow" of the scree plot rule of thumb for minimum percentage of variation, we would retain the first components. (type a numerical answer e.g. 9)
There are 39 observations representing the 39 Peruvians in the dataset and 10 variables. Principal Component Analysis was performed on the data set, giving the following result based on the correlation matrix. Component eValue Total 1 3.449237 40.00% 2 1.692153 35.00% 3 1.543212 4 0.856276 5 0.783724 6 0.606369 7 0.438018 8 0.328671 9 0.205767 10 0.096575 10 30.00% 25.00% 20.00% 15.00% 10.00% 5.00% 0.00% 3 Scree Plot 4 5 6 9 10 Based on the "detect the elbow" of the scree plot rule of thumb for minimum percentage of variation, we would retain the first components. (type a numerical answer e.g. 9)
MATLAB: An Introduction with Applications
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ISBN:9781119256830
Author:Amos Gilat
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Transcribed Image Text:There are 39 observations representing the 39 Peruvians in the dataset and 10 variables.
Principal Component Analysis was performed on the data set, giving the following result based
on the correlation matrix.
Component eValue
1 3.449237
2 1.692153
3
1.543212
4 0.856276
5 0.783724
6 0.606369
7 0.438018
8 0.328671
9 0.205767
10 0.096575
Total
10
40.00%
35.00%
30.00%
25.00%
20.00%
15.00%
10.00%
5.00%
0.00%
12
3
Scree Plot
4
5
9
10
Based on the "detect the elbow of the scree plot rule of thumb for minimum percentage of
variation, we would retain the first
components. (type a numerical answer e.g. 9)
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