Question
Study the following output for Principal component analysis on heptathlon data and answer the following questions. Output: Importance of components: PC1PC2PC3PC4PC5PC6 Standard deviation2.11191.09280.721810.676140.495240.27010 Proportion of
Study the following output for Principal component analysis on "heptathlon" data and answer the following questions.
Output:
Importance of components:
PC1PC2PC3PC4PC5PC6
Standard deviation2.11191.09280.721810.676140.495240.27010
Proportion of Variance0.63720.17060.074430.065310.035040.01042
Cumulative Proportion0.63720.80780.882230.947540.982580.99300
PC7
Standard deviation0.2214
Proportion of Variance0.0070
Cumulative Proportion1.0000
1) If you want to take into account almost 95% variability in the data then how many principal components will you choose?
a) 1 b) 2 c) 3 d) 4
2) Now if you use Kaiser's criterion of selecting optimal number of Principal components then how many principal components will you choose?
a)1 b) 2 c) 3 d) 4
3) In principal component analysis what is the angle between principal components'?
a)00 b) 450 c) 900 d) >450
4) In order to perform factor analysis on a dataset having dispersion matrix ?, we must have,
a) ? = I, b) ? ? I c) ? can be anything d) None.
5) What can you say about Promax and Varimax rotations in Factor Analysis?
a) Factors obtained in both rotation methods are orthogonal (perpendicular).
b) Factors obtained in both rotation methods are not orthogonal.
c) Factors obtained in Promax rotation are orthogonal whereas factors obtained in Varimax rotation are not.
d) Factors obtained in Varimax rotation are orthogonal whereas factors obtained in Promax rotation are not.
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