6 observations and p = 9 variables was analysed to reduce its dimensionality. The following is a list of order, that is d₁, d₂,..., dg: 399.1338, 192.1412, 173.0043, 161.6635, 158.0541, 146.6826, 140.0039, 134. rical value of the eigenvalue 4 of Σ. This eigenvalue is located in the position (4,4) of the matrix A ar PC4: ntage of total variability explained by the Principal component PC4. The number you write should be be s in your answer. explained has been set at 80%. How many principal components must you select? Write your answer (in
6 observations and p = 9 variables was analysed to reduce its dimensionality. The following is a list of order, that is d₁, d₂,..., dg: 399.1338, 192.1412, 173.0043, 161.6635, 158.0541, 146.6826, 140.0039, 134. rical value of the eigenvalue 4 of Σ. This eigenvalue is located in the position (4,4) of the matrix A ar PC4: ntage of total variability explained by the Principal component PC4. The number you write should be be s in your answer. explained has been set at 80%. How many principal components must you select? Write your answer (in
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A centered dataset with n = 116 observations and p = 9 variables was analysed to reduce its dimensionality. The following is a list of singular
eigenvalues of X in decreasing order, that is d₁, d2, . . . , dg: 399.1338, 192.1412, 173.0043, 161.6635, 158.0541, 146.6826, 140.0039, 134.1633, 121.1941.
A) Compute and write the numerical value of the eigenvalue 4 of Σ. This eigenvalue is located in the position (4, 4) of the matrix A and is simultaneously
the sample variance of the score PC4:
B) Compute and write the percentage of total variability explained by the Principal component PC4. The number you write should be between 0 and 100
and you should include decimals in your answer.
C) A threshold of total variability explained has been set at 80%. How many principal components must you select? Write your answer (integer value).
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