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Optimizing, Bayesian Analysis, and Time Series

by | Dec 1, 2023 | Posted Questions

Optimizing, Bayesian Analysis, and Time Series

1. If events are not mutually exclusive, which of the following are true?
A) P(A or B) = P(A) + P(B) – P(A and B)
B) P(A or B) = P(A) * P(B)
C) P(A or B) = P(A) + P(B)
D) P(A or B) = P(A|B) * P(B)
E) none of the above

2. Which of the following would you use to optimize your investment when constraints apply?
A) linear programming
B) decision tree
C) forecasting
D) simulation
E) none of the above

3. Z is which of the following:
A) used to convert the Poisson distribution to the standard normal distribution.
B) the number of standard deviations from X to the mean.
C) always positive.
D) all of the above

4. Bayesian analysis involves:
A) additional information
B) posterior probability
C) statistical dependency
D) all of the above
E) none of the above

5. Moving average time series forecasting doesn’t require which of the following as a prerequisite?
A) forecast for time period in question.
B) actual demand in previous time periods.
C) n as number of periods to average.
D) requires all of the above

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