Decision Science | Chapter 5 | Part 3 | MBA MCQs | DS

Decision Science MCQs

  

 

1. A particular result of an experiment is called:
   1.   Trial
   2.   Outcome
   3.   Compound event
   4.   Simple event
2. A collection of one or more outcomes of an experiment is called:
   1.   Event
   2.   None of the above
   3.   Sample point
   4.   Outcome
3. A process that leads to the occurrence of one and only one of several possible observations is called:
   1.   Random experiment
   2.   Experiment
   3.   Probability distribution
   4.   Random variable
4. Which statement is false?
   1.   The classical definition applies when there are n equally likely outcomes to an experiment
   2.   The empirical definition occurs when number of times an event happen is divided by the number
      of observations.
   3.   A subjective probability is based on whatever information is available
   4.   The general rule of addition is used when the events are mutually exclusive
5. The term 'sample space' is used for:
   1.   Sample
   2.   All possible outcomes
   3.   All possible coins
   4.   Probability
6. The term 'event' is used for:
   1.   Time
   2.   Total number of outcomes
   3.   Probability
   4.   A sub-set of the sample space
7. The six faces of the die are called equally likely if the die is:
   1.   Round
   2.   Small
   3.   Fair
   4.   Six-faced
8. If we toss a coin and P(H) = 2P(T), then probability of head is equal to:
   1.   0
   2.   1/2
   3.   1/3
   4.   2/3
9. A letter is chosen at random from the word "Statistics". The probability of getting a vowel is:
   1.   1/10
   2.   2/10
   3.   3/10
   4.   4/10
10. An arrangement in which the order of the objects selected from a specific pool of objects is important
    called:
    1.   Combination
    2.   Sample space
    3.   Factorial
    4.   Permutation
11. Two fair dice are rolled. The probability of throwing an odd sum is:
    1.   1/2
    2.   1/6
    3.   1/36
    4.   1
12. Given P(A) = 0.4, P(B) = 0.5 and P(A⋃B)=0.9,then:
    1.   A and B are not mutually exclusive events
    2.   A and Bare independent events
    3.   A and B are mutually exclusive events
    4.   A and B are equally likely events
13. If P(B/A) = 0.50 and P(A⋂B) = 0.40, then p(A) will be equal to:
    1.   0.40
    2.   0.50
    3.   0.80
    4.   1
14. If P(A/B) = P(A) and P(B/A)=P(B), then A and B are:
    1.   Mutually exclusive
    2.   Equally likely
    3.   Independent
    4.   Dependent
15. If A and B are two mutually exclusive and exhaustive events and P(A)=2P(B), then P(B) is equal to:
    1.   1/2
    2.   2/3
    3.   1/3
    4.   1/4
16. Two coins are tossed. Probability of getting head on the first coin is:
    1.   2/4
    2.   4
    3.   0
    4.   1
17. A die and a coin are tossed together. Probability of getting head on the coin is:
    1.   6/12
    2.   6
    3.   12
    4.   0
18. If A and B are two not-independent events, then the probability that both A and B will happen
    together is:
    1.   P(A⋂B) = P(A)P(B/A) (b)
    2.   P(A⋂B) = P(A)P(B)
    3.   P(A⋂B) = P(A)+P(B)
    4.   P(A⋂B) = P(A)
19. Given P(A)=2/3, P(B)=3/8 and PAB)=1/4, then A and B are:
    1.   Independent
    2.   Dependent
    3.   Mutually exclusive
    4.   Equally likely
20. If A and B are any two events, then P(A/B)+P( /B) is equal to:
    1.   0
    2.   0.25
    3.   0.5
    4.   1