1.Conduct principal component analysis on all variables except the Name variable. Should you standardize the data? Explain. 2. What percentage of total variability is accounted for by the first principal component? How many principal components must be retained in order to account for at least 80% of the total variance in the data? 3. Which original variables are given the highest weight to compute the first principal component? Which original variable is given the highest weight to compute the second principal component? 4. What is the principal component 1 score for the first record (3M)?
1.Conduct principal component analysis on all variables except the Name variable. Should you standardize the data? Explain. 2. What percentage of total variability is accounted for by the first principal component? How many principal components must be retained in order to account for at least 80% of the total variance in the data? 3. Which original variables are given the highest weight to compute the first principal component? Which original variable is given the highest weight to compute the second principal component? 4. What is the principal component 1 score for the first record (3M)?
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
Related questions
Question
1.Conduct principal component analysis on all variables except the Name variable. Should you
standardize the data? Explain.
2. What percentage of total variability is accounted for by the first principal component? How many
principal components must be retained in order to account for at least 80% of the total variance in the data?
3. Which original variables are given the highest weight to compute the first principal component?
Which original variable is given the highest weight to compute the second principal component?
4. What is the principal component 1 score for the first record
(3M)?
Transcribed Image Text:Principal Components
Feature Component
Price
Dividend
PE
EPS
Book Value
52 week low
52 week high
Market Cap
EBITDA
Explained Variance
Component
Component 1
Component 2
Component 3
Component 4
Component 5
Component 6
Component 7
Component 8
Component 9
Component 1 Component 2 Component 3
0.485983579 0.025780889
-0.132101522 -0.210564648
0.039149067 0.168043392
0.407515194 -0.092833453
0.335715426 0.045529786
0.475145835
0.0194489
0.486955155 0.033733938
0.051408656 -0.665616655
0.023049537 -0.686663318
Eigenvalue
Component 4 Component 5 Component 6 Component 7 Component 8 Component 9
-0.142079046 -0.009862657 0.194173575 0.135304911
0.0765984 -0.539084935
0.62480469
-0.09098199 -0.953338445 0.095718905 0.063441765 -0.078700194 -0.040658264 0.006783906
-0.822096945 -0.002072718 -0.354780218 -0.32736604 -0.246509915 0.023007406
0.402814572 -0.069748359 -0.00020856 -0.583945795 -0.558668226 0.065287002
0.24190631 -0.17489509 -0.836137412 0.16937449 0.260035529 0.025972886
-0.173269999 -0.062534635 0.260900165 0.15623748 0.160273252 0.778347159
-0.133396646 -0.034623516 0.198303496 0.098298334 0.079352932 -0.308301314
-0.123775826 0.208505527 -0.14382808 0.493009759 -0.480390613 0.025608628
-0.108519955 0.083708965 -0.007746406 -0.472956082 0.533557513 -0.027170058
0.006861478
0.028698255
0.002946171
0.126230902
-0.769681635
-0.018453378
0.003023478
Variance, %
3.959989888 43.99988765
1.872697098
20.80774554
1.2299826 13.66647333
0.913350818 10.14834243
0.61853115 6.872568332
0.1993361 2.214845551
0.173455677 1.927285297
0.021744329 0.241603659
0.01091234
0.121248219
Cumulative Variance, %
43.99988765
64.80763318
78.47410652
88.62244894
95.49501727
97.70986283
99.63714812
99.87875178
100,
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