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NEW QUESTION: 1
The difference between true severity and the best approximation of the true severity is called:
A. Approximation error
B. Estimation error
C. Total error
D. Fitting error
Answer: A
Explanation:
Explanation
This question relates to fitting a distribution to the true severity of the operational risk loss we are trying to model. The quality of the fit, or the precision of the fit, has two elements to the difference between the severity as represented by our model and the true severity. To understand this, consider the three data points below:
a. The true severity,
b. The best approximation of the true severity in the model space, and
c. The fit based on the dataset.
- True severity is what we are trying to model.
- The model space refers to the collection of analytical distributions (log-normal, burr etc) that we are considering to arrive at the estimate of the severity.
- The 'best approximation of the true severity in the model space' is reached by estimating the parameters of the distribution that optimizes the risk functional.
- The 'fit' is the actual parameter estimates we settle for with the distribution we have determined best fits the true estimate of our severity. When estimating parameters, we have various methods available for estimation - the least squares method, the maximum likelihood method, for example, and we can get different estimates depending upon the method we choose to use.
Our severity model will be different from the true severity, and the total difference can be split into two types of errors:
1. Fitting error, represented by 'c - b' above: The difference between the fit based on the dataset and the best approximation of the true severity is called 'fitting error', ie, a measure of the extent to which we could have estimated the parameters better.
2. Approximation error, represented by 'b - a' above: Approximation error is the difference between the true severity, and the best approximation of the true severity that can be achieved within the model space is called
'approximation error'.
One can reduce the approximation error by expanding the model space by adding more distributions. This will reduce the approximation error, but generally has the effect of increasing the fitting error because the complexity of the model space increases, and there are more ways to fit to the true severity.

NEW QUESTION: 2
An Isilon cluster with three S210 nodes and three NL400 nodes was expanded to 18 nodes (15 x S210, 3 x NL400). You have been asked to revise the data protection policy initially set to N+3d:1n while optimizing the available writable disk space.
What is the recommended data protection strategy for each pool and will the data protection overhead average increase or decrease?
A. S210 node pool changes to N+2d:1n NL400 node pool changes to N+2d:1n
B. S210 node pool changes to N+2n NL400 node pool remains N+3d:1n
C. S210 node pool remains N+3d:1n NL400 node pool changes to N+2d:1n
D. S210 node pool remains N+3d:1n NL400 node pool changes to N+2n
Answer: A

NEW QUESTION: 3
Which statement is false about mapping Learning Plans to users?
A. They can be configured to allow users to add themselves to the plan and be dynamically mapped to users based on Group membership.
B. They can be mapped to users by mapping the plan to a Job Profile and then mapping users to the Job Profile.
C. They can be mapped to the user using Training Offerings.
D. They can only be mapped to users who are members of the LearnCenter in which the plan wascreated.
E. They can be mapped to users by Supervisors granted the appropriate permissions.
Answer: B

NEW QUESTION: 4
What is a step in configuring the ToR data switches for a Dell EMC PowerStore X?
A. Configure a port for the discovery laptop
B. Create node A port-channel
C. Create VLANs for NAS servers
D. Configure LACP uplink to management switch
Answer: C
Explanation:
Reference:
https://www.dell.com/support/manuals/pk/en/pkbsd1/powerstore-9000t/pwrstr-ntwk-cfg/configure- port-interfaces-for-powerstore-x-model-node-connectivity?guid=guid-ef6b40ef-82a3-4ebf-99bf- a7bea8d6a586&lang=en-us