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NEW QUESTION: 1
Given the following:
Measures (Dense): 40 stored members, 50 total members
Time (Dense): 17 stored members, 17 total members
Scenario (Dense): 2 stored members, 5 total members
Market (Sparse): 100 stored members, 100 total members
Product (Sparse): 500 stored members, 550 total members
How many potential blocks could be created?
A. Potential Blocks = 100 * 550 * 8
B. Potential Blocks = 40 * 17*2
C. Potential Blocks = 100 * 500 * 8
D. Potential Blocks = 100 * 550
E. Potential Blocks = 100 * 500
F. Potential Blocks = 40* 17*2*8
Answer: E
Explanation:
The number of stored members in sparse Dimensions will help us in finding potential number of blocks
Potential Number of Blocks = Stored Members in Market * Stored Products in Scenario.

NEW QUESTION: 2
You successfully compromise a target system's web application using blind command injection. The command you injected is ping-n 1 192.168.1.200. Assuming your machine is 192.168.1 200, which of the following would you see?
A. Ping-n 1 192.168.1 200 on the compromised system
B. An ICMP Echo packet on your sniffer containing the source address of the target
C. A 'Destination host unreachable' error message on the compromised system
D. A packet containing 'Packets: Sent - 1 Received = 1, Loss = 0 (0% loss) on yoursniffer
Answer: A

NEW QUESTION: 3
Which option would be the primary concern of a CIO who is focused on advanced protection in the advanced protection use case?
A. Reduce vulnerabilities
B. Integrate solutions seamlessly
C. Onboard devices quickly
D. Expand into new markets
Answer: A
Explanation:
Explanation/Reference:
Explanation:

NEW QUESTION: 4
Suppose your company produces roofing shingles. You have a chart which shows housing starts which is the (independent variable) and shingle sales which is the (dependent) variable. The usage of shingles can be attributed to housing starts. In forecasting which model would BEST fit your analysis?
A. Future sales based on past sales
B. Winters model
C. Least squares/regression model
D. Box-Jenkins model
Answer: C
Explanation:
Suppose your company produces roofing shingles. You have a chart which shows housing starts which is the (independent variable) and shingle sales which is the (dependent) variable. The usage of shingles can be attributed to housing starts. In forecasting the last squares/regression model would
BEST fit your analysis. The Box-Jenkins model involves lag and shift measures and uses auto-regressive integrated moving average (ARIMA). Future sales based on past sales is a life cycle analogy and the winters model is a trend adjusted model using gamma.

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