Decision Science | Chapter 5 | Part 1 | MBA MCQs | DS

The the special rule of multiplication of probability, the events must be
Decision Science MCQs

  

 

1. The distribution function F(X) is represented by
   1.   P(X=x)
   2.   P(X)
   3.   P(X>x)
   4.   P(X≤x)
2. For distribution Function F(X), F(−∞)=0 and F(∞)=?
   1.   0
   2.   -1
   3.   1
3. A discrete probability distribution may be represented by
   1.   A table
   2.   A graph
   3.   A mathematical Equation
   4.   All of these
4. Total Area under the curve in probability of density function is
   1.   0
   2.   1
   3.   -1
   4.   Infinity
5. What is the probability that a ball drawn at random from a jar?
   1.   0.1
   2.   1
   3.   .5
   4.   0
   5.   Cannot be determined from given information
6. Probability of occurrence of an event lies between
   1.   -1 and 0
   2.   0 and 1
   3.   -1 and 1
   4.   exactly 1
7. Probability distribution of a random variable is also known as
   1.   Probability
   2.   Probability Function
   3.   Distribution Function
   4.   Probability Density Function
8. The probability function is always
   1.   Negative
   2.   Non Negative
   3.   Infinity
   4.   None
9. Which of the following is not a correct statement about a probability.
   1.   It must have a value between 0 and 1
   2.   A value near 0 means that the event is not likely to occur/happens
   3.   It can be reported as a decimal or a fraction
   4.   It is the collection of several experiments
10. If the occurrence of one event means that another cannot happen, then the events are
    
    1.   Independent
    2.   Bayesian
    3.   Mutually Exclusive
    4.   Empirical
11. Which of the following is not a condition of the binomial distribution?
    
    1.   Only 2 possible outcomes
    2.   must have at least 3 trials
    3.   have constant probability of success
    4.   trials must be independent
12. In which approach to probability the outcomes are equally likely to occur?
    1.   Classical Probability
    2.   Relative Frequency
    3.   Subjective Probability
    4.   Independent
13. A listing of the possibile outcomes of an experiment and their corresponding probability is called
    
    1.   Random Variable
    2.   Probability distribution
    3.   Bayesian table
    4.   Contingency table
14. In special rule of addition of probability, the events are always
    
    1.   Independent events
    2.   Mutually Exclusive events
    3.   Empirical
    4.   Bayesian
15. The collection of one or more outcomes from an experiment is called
    
    1.   Probability
    2.   Random Variable
    3.   Random Experiment
    4.   Z-Value
    5.   Event
16. The the special rule of multiplication of probability, the events must be
    
    1.   Independent
    2.   Empirical
    3.   Bayesian
    4.   Mutually exclusive
17. Which of the following is not an example of a discrete probability distribution?
    
    1.   The sale or purchase price of a house
    2.   Whether or not a home has a swimming pool in it.
    3.   The number of bathrooms in a house
    4.   The number of bedrooms in a house
18. If a card is chosen from a standard deck of cards, what is the probability of getting a five or a seven?
    
    1.   4/52
    2.   1/169
    3.   8/52
    4.   1/26
19. The joint probability is
    1.   The likelihood of two events happening together
    2.   Based on two mutually exclusive events
    3.   Also called Prior probability
    4.   The likelihood of an event happening given that another event has already happened
20. If you roll a pair of dice, what is the probability that (at least) one of the dice is a 4 or the sum of the dice is 7?
    
    1.   4/36
    2.   21/36
    3.   13/36
    4.   15/36