Decision Science | Chapter 2 | Part 5 | MBA MCQs | DS

Decision Science MCQs

  

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1. The phenomenon in which customers join a line but leave after some time because they are too impatient to wait for their turn is called
   1.   Renege
   2.   Debalking
   3.   Derenege
   4.   Balking
2. Values for the probabilistic inputs to a simulation
   1.   are selected by the decision maker
   2.   are controlled by the decision maker
   3.   are randomly generated based on historical information
   4.   are calculated by fixed mathematical formulas
3. The inputs required for Markov process include
   1.   Initial condition of the market
   2.   both
   3.   transition probabilities
   4.   none of these
4. Markov analysis is a technique that deals with the probabilities of future occurrences by
   1.   using Bayes' theorem
   2.   time series forecasting
   3.   analyzing presently known probabilities
   4.   the maximal flow technique
5. A simulation model uses the mathematical expressions and logical relationships of the
   1.   real system
   2.   computer model
   3.   estimated inferences
   4.   performance measures
6. ………. Theory is an important operations research technique to analyze the queuing behavior
   1.   Network
   2.   Decision
   3.   Simulation
   4.   Waiting line
7. Analysis of a Markov process
   1.   All of the alternatives are true
   2.   optimizes the system
   3.   leads to higher order decision making
   4.   describes future behavior of the system
8. In Markov analysis, we are concerned with the probability that the
   1.   transition will occur
   2.   time has reached a steady state
   3.   state is part of a system
   4.   system is in a particular state at a given time
9. Which of the following statements is INCORRECT regarding the advantages of simulation?
   1.   Simulation guarantees an optimal solution
   2.   Simulation guarantees an optimal solution
   3.   A simulation model provides a convenient experimental laboratory for the real system
   4.   Simulation is relatively easy to explain and understand
10. While considering the queuing models we have considered …. distribution for service time
    1.   Exponential
    2.   Chi-square
    3.   Normal
    4.   Binomia
11. Cumulative probabilities are found by
    1.   any method one chooses
    2.   summing all the probabilities associated with a variable
    3.   summing all the previous probabilities up to the current value of the variable
    4.   simulating the initial probability distribution
12. In a transition probability matrix
    1.   The sum of each row is 0
    2.   The sum of each row is 1
    3.   The sum of each column is 0
    4.   The sum of each column is 1
13. Simulation is a
    1.   Descriptive technique
    2.   none of these
    3.   Optimizing technique
    4.   both
14. A sequence of transitions beginning in state i and ending in state j is called as
    1.   transition from i to j
    2.   transition from 0 to j
    3.   transition from j to i
    4.   transition from 0 to i
15. As simulation is not an analytical model therefore result of simulation must be viewed as
    1.   Exact
    2.   Approximation
    3.   Simplified
    4.   Unrealistic
16. In a market with three brands with equal shares the initial condition can be shown by
    1.   [0.5 0.25 0.25]
    2.   [0.25 0.25 0.25]
    3.   [a b c]
    4.   [1/3 1/3 1/3]
17. A random number generator provides numbers those are
    1.   Selected by giving equal chance to all the available range of numbers
    2.   In a increasing sequence
    3.   In a decreasing sequence
    4.   In orderly fashion
18. Markov analysis assumes that conditions are both
    1.   collectively exhaustive and mutually exclusive
    2.   collectively dependent and mutually exclusive
    3.   collectively dependent and complementary
    4.   complementary and collectively exhaustive
19. In Markov analysis, the likelihood that any system will change from one period to the next is revealed by the
    1.   matrix of state probabilities
    2.   transition-elasticity
    3.   matrix of transition probabilities
    4.   identity matrix