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NEW QUESTION: 1
Fill in the blank in the following sentence:
Principal component analysis (PCA) is a statistical tool to decompose a ____________ matrix into its principal components and is useful in risk management to reduce dimensions.
A. Correlation
B. Covariance
C. Positive semi-definite
D. Volatility
Answer: C
Explanation:
Explanation
PCA is a statistical tool that decomposes a positive semi-definite matrix into its principal components. The first few principal components explain nearly all the variation and other components can then be ignored as they are too small in the larger picture. PCA in risk management is applied to a positive semi-definite correlation or covariance matrix to reveal the principal components that cause the variation. By allowing a focus on a few components, PCA reduces dimensionality.
While performing the math of PCA is unlikely to be asked in the PRMIA exam, you should remember that principal components have the additional property of being uncorrelated to each other which makes it useful as it is possible to vary one of the components without having to worry about the effect of that on the other components.

NEW QUESTION: 2

A. Option C
B. Option B
C. Option E
D. Option A
E. Option D
Answer: A

NEW QUESTION: 3
You have a Microsoft Azure Data Factory that recently ran several activities in parallel.
You receive alerts indicating that there are insufficient resources.
From the Activity Windows list in the Monitoring and Management app, you discover the statuses described in the following table.

Which activity cannot complete because of insufficient resources?
A. Activity7
B. Activity4
C. Activity2
D. Activity5
Answer: D