MCQOPTIONS
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MCQOPTIONS
This section includes 64 Mcqs, each offering curated multiple-choice questions to sharpen your Business Statistics knowledge and support exam preparation. Choose a topic below to get started.
| 1. |
Considering the events Y and Z, the non-occurrence of event Z and the occurrence of event Y is represented by |
| A. | Y-bar union Z |
| B. | Y union Z-bar |
| C. | Y-bar intersection Z |
| D. | Y intersection Z-bar |
| Answer» E. | |
| 2. |
If the number of outcomes in collection are 5 and the distinct outcomes are 9 then the count value according to combinations method is |
| A. | 4 |
| B. | 9 |
| C. | 126 |
| D. | 45 |
| Answer» D. 45 | |
| 3. |
In a Venn diagram used to represent probabilities, the sample space of events is represented by |
| A. | square |
| B. | triangle |
| C. | circle |
| D. | rectangle |
| Answer» E. | |
| 4. |
The joint probability of two statistical dependent events Y and Z can be written as P(Y and Z) = |
| A. | P(Z + Y) * P(Y|Z) |
| B. | P(Y) * P(Z|Y) |
| C. | P(Y) * P(Z|Y) + P(Z) |
| D. | P(Y) * P(Z|Y) - P(Z + Y) |
| Answer» C. P(Y) * P(Z|Y) + P(Z) | |
| 5. |
The important rules in computation of experimental outcomes includes |
| A. | multiple experiments |
| B. | permutations |
| C. | combinations |
| D. | all of above |
| Answer» E. | |
| 6. |
The outcome of experiment which can be broken into more convenient list of outcomes is called |
| A. | alpha event |
| B. | gamma event |
| C. | simple event |
| D. | random event |
| Answer» D. random event | |
| 7. |
In a Venn diagram used to represent probabilities, the occurred events are represented by |
| A. | circle |
| B. | rectangle |
| C. | square |
| D. | triangle |
| Answer» B. rectangle | |
| 8. |
Considering the combination rule of counting the outcome, the value of 5! Is |
| A. | 5 |
| B. | 120 |
| C. | 24 |
| D. | 20 |
| Answer» C. 24 | |
| 9. |
The method of counting the outcomes in which the number of outcomes are determined while considering the ordering is classified as |
| A. | intersection combinations |
| B. | union combinations |
| C. | listed combination |
| D. | permutations |
| Answer» E. | |
| 10. |
The method of counting the outcomes in which the number of outcomes are determined without prior listing is classified as |
| A. | single experiments |
| B. | multiple experiments |
| C. | zero experiments |
| D. | unlisted experiments |
| Answer» C. zero experiments | |
| 11. |
The probability without any conditions of occurrence of an event is considered as |
| A. | conditional probability |
| B. | marginal probability |
| C. | non conditional probability |
| D. | occurrence probability |
| Answer» C. non conditional probability | |
| 12. |
The method in which the previously calculated probabilities are revised with new probabilities is classified as |
| A. | updating theorem |
| B. | revised theorem |
| C. | Bayes theorem |
| D. | dependency theorem |
| Answer» D. dependency theorem | |
| 13. |
Consider two events X and Y, the X-bar and Y-bar represents |
| A. | occurrence of Y |
| B. | occurrence of X |
| C. | non-occurrence of X and Y |
| D. | occurrence of X and Y |
| Answer» D. occurrence of X and Y | |
| 14. |
If a bag contains three fruits, 16 percent are apples, 30 percent are oranges and 20 percent some other fruit that is neither oranges nor apples then the probability of selecting an orange randomly is |
| A. | 0.3 |
| B. | 0.45 |
| C. | 0.65 |
| D. | 0.034 |
| Answer» B. 0.45 | |
| 15. |
The difference between sample space and subset of sample space is considered as |
| A. | numerical complementary events |
| B. | equal compulsory events |
| C. | complementary events |
| D. | compulsory events |
| Answer» D. compulsory events | |
| 16. |
The variation in which outcomes of experiments are effected by uncontrolled factors is considered as |
| A. | random variation |
| B. | mesokurtic variation |
| C. | platykurtic variation |
| D. | mesokurtic variation |
| Answer» B. mesokurtic variation | |
| 17. |
The type of probability approach in which the event A is the ratio explaining the number of times event A is occurred in experiments is classified as |
| A. | counted probability distribution |
| B. | relative frequency approach |
| C. | irrelative frequency approach |
| D. | fixed probability distribution |
| Answer» C. irrelative frequency approach | |
| 18. |
The types of probabilities for independent events must includes |
| A. | joint events |
| B. | marginal events |
| C. | conditional events |
| D. | all of above |
| Answer» E. | |
| 19. |
The outcomes of an experiment are classified as |
| A. | logged events |
| B. | exponential results |
| C. | results |
| D. | events |
| Answer» E. | |
| 20. |
If two events G and H are classified as joint events then the events are represented as |
| A. | G * H |
| B. | G + H |
| C. | G intersection H |
| D. | G union H |
| Answer» D. G union H | |
| 21. |
If the occurrence of one event affects or explains the occurrence of other event then the events are classified as |
| A. | known events |
| B. | unknown events |
| C. | independent events |
| D. | dependent events |
| Answer» E. | |
| 22. |
If in an experiment the A and B are two events, then the occurrence of event A or B simultaneously is represented by |
| A. | A intersection B |
| B. | A + B |
| C. | A - B |
| D. | A union B |
| Answer» B. A + B | |
| 23. |
If two events X and Y are considered as partially overlapping events then the rule of addition can be written as |
| A. | P(X or Y) = P(X) - P(Y) + P(X and Y) |
| B. | P(X or Y) = P(X) + P(Y) * P(X - Y) |
| C. | P(X or Y) = P(X) * P(Y) + P(X - Y) |
| D. | P(X or Y) = P(X) + P(Y) - P(X and Y) |
| Answer» E. | |
| 24. |
In measuring the probability of any certain event, the one which is in the limit of probability represents |
| A. | certain event |
| B. | sample event |
| C. | impossible events |
| D. | possible events |
| Answer» B. sample event | |
| 25. |
For the mutually exclusive events, the formula of calculating probability as n(A) ⁄ n(S) + n(B) ⁄ n(S) is used for |
| A. | rule of marginal count |
| B. | rule of comparison |
| C. | rule of addition |
| D. | rule of division |
| Answer» D. rule of division | |
| 26. |
If the occurrence of a statistical event A does not affect the occurrence of event B and vice versa then these events are classified as |
| A. | statistically dependent events |
| B. | descriptive unaffected events |
| C. | statistically independent events |
| D. | statistically unaffected events |
| Answer» D. statistically unaffected events | |
| 27. |
The number of individuals arriving at boarding counter on an airport is an example of |
| A. | numerical outcome |
| B. | non numerical outcome |
| C. | random outcome |
| D. | simple outcome |
| Answer» B. non numerical outcome | |
| 28. |
The marginal probability of independent events and dependent events must be |
| A. | same |
| B. | different |
| C. | one |
| D. | two |
| Answer» B. different | |
| 29. |
The previous probabilities in Bayes Theorem that are changed with the help of new available information are classified as |
| A. | independent probabilities |
| B. | posterior probabilities |
| C. | interior probabilities |
| D. | dependent probabilities |
| Answer» C. interior probabilities | |
| 30. |
If a brown sack consists of 4 white balls and 3 black balls then the probability of one randomly drawn ball will be white is |
| A. | 4 ⁄ 7 |
| B. | 1 ⁄7 |
| C. | 4 ⁄ 4 |
| D. | 4 ⁄ 3 |
| Answer» B. 1 ⁄7 | |
| 31. |
In measuring the probability of any certain event, the zero represents |
| A. | impossible events |
| B. | possible events |
| C. | certain event |
| D. | sample event |
| Answer» B. possible events | |
| 32. |
In probability theory, the events are denoted by |
| A. | Greek letters |
| B. | capital letters |
| C. | small letters |
| D. | Latin letters |
| Answer» C. small letters | |
| 33. |
The conditional probability of two independent events Y and Z can be written as |
| A. | P(Y - Z) |
| B. | P(Y * Z) |
| C. | P(Y|Z) |
| D. | P(Y + Z) |
| Answer» D. P(Y + Z) | |
| 34. |
For two events, the probability of occurrence of both events at same time or occurrence in series is classified as |
| A. | joint probability |
| B. | dependent probability |
| C. | series probability |
| D. | conditional probability |
| Answer» B. dependent probability | |
| 35. |
The probability of the event A that does not occur in experiment is equal to |
| A. | 1 - P(A) |
| B. | 1 + P(A) |
| C. | 1 × P(A) |
| D. | 2 - P(A) |
| Answer» B. 1 + P(A) | |
| 36. |
The payments received by cheques or cash is an example of |
| A. | numerical outcome |
| B. | non numerical outcome |
| C. | random outcome |
| D. | simple outcome |
| Answer» C. random outcome | |
| 37. |
If a coin is tossed one time then the probability of occurrence of heads is |
| A. | 1⁄2 |
| B. | 1⁄1 |
| C. | 2⁄1 |
| D. | 2⁄2 |
| Answer» B. 1⁄1 | |
| 38. |
The events in which some points of sample are common are considered as |
| A. | divisional events |
| B. | overlapping events |
| C. | common events |
| D. | additive events |
| Answer» C. common events | |
| 39. |
If the number of outcomes in collection are 2 and the distinct outcomes are 4 then the count value according to permutations is |
| A. | 2 |
| B. | 12 |
| C. | 24 |
| D. | 4 |
| Answer» D. 4 | |
| 40. |
If the factory has four machines, machines will be completely depreciated in next year and the chances of failure of all machines respectively are 0.24, 0.45, 0.35, 0.38 then the probability of failure of all machines before next year is |
| A. | 0.355 |
| B. | 0.148 |
| C. | 0.158 |
| D. | 0.168 |
| Answer» E. | |
| 41. |
If a person buys a lottery, the chance of winning a Toyota car is 60%, the chance of winning Hyundai car is 70% and the chance of winning both is 40% then chance of winning Toyota or Hyundai is |
| A. | 0.6 |
| B. | 0.9 |
| C. | 0.8 |
| D. | 0.5 |
| Answer» C. 0.8 | |
| 42. |
In probability theories, the collection of all the events possible outcomes from an experiment is classified as |
| A. | mutually exclusive events |
| B. | collectively exhaustive events |
| C. | collectively exclusive events |
| D. | mutually exhaustive events |
| Answer» C. collectively exclusive events | |
| 43. |
Consider an event B, the non-occurrence of event B is represented by |
| A. | union of A |
| B. | complement of A |
| C. | intersection of A |
| D. | A is equal to zero |
| Answer» C. intersection of A | |
| 44. |
The occurrence of two events in a way that events have some connection in between is classified as |
| A. | compound events |
| B. | mutual events |
| C. | connected events |
| D. | interlinked events |
| Answer» B. mutual events | |
| 45. |
The sample space for the experiment in which two coins are tossed is |
| A. | 4 |
| B. | 8 |
| C. | 2 |
| D. | 10 |
| Answer» B. 8 | |
| 46. |
If the probability of an event depends on repetitive observations that occurs in outcomes of experiment then this is classified as |
| A. | fixed probability |
| B. | non-relative probability |
| C. | empirical probability |
| D. | relative probability |
| Answer» D. relative probability | |
| 47. |
If in an experiment the A and B are two events, then the occurrence of event B or event A or occurrence of both is represented by |
| A. | A - B |
| B. | A union B |
| C. | A intersection B |
| D. | A + B |
| Answer» C. A intersection B | |
| 48. |
The measure of chance of an uncertain event in the form of numerical figures is classified as |
| A. | probability |
| B. | variability |
| C. | durability |
| D. | likelihood |
| Answer» B. variability | |
| 49. |
Considering the events Y and Z, the occurrence of Z and the non-occurrence of Y is represented by |
| A. | Y-bar union Z |
| B. | Z-bar union Y |
| C. | Y-bar intersection Z |
| D. | Z-bar intersection Y |
| Answer» D. Z-bar intersection Y | |
| 50. |
The event such as equal chance of heads or tails while tossing the coin is an example of |
| A. | numerical events |
| B. | equally likely events |
| C. | unequal events |
| D. | non-numerical events |
| Answer» C. unequal events | |