Chapter 5 MCQ - Practice MCQ PDF

Preview

Summary

PROBABILITY1 which approach to probability the outcomes are equally likely to occur?a. Subjective Probability b. Relative Frequency c. Independent d. Classical probability 2. If a card is chosen from a standard deck of cards, what is the probability of getting a five or a seven?a. 4/ b. 1/ c. 8/ d. ...

Description

PROBABILITY 1.In which approach to probability the outcomes are equally likely to occur? a. Subjective Probability b. Relative Frequency c. Independent d. Classical probability 2. If a card is chosen from a standard deck of cards, what is the probability of getting a five or a seven? a. 4/52 b. 1/26 c. 8/52 d. 1/69 3. Which of the following is not an example of a discrete probability distribution? a. The number of bedrooms in a house b. The number of bathrooms in a house c. The sale or purchase price of a house d. Whether or not a home has swimming pool in it 4. Which of the following is not a correct statement about a probability. a. It must have a value between 0 and 1. b. It can be reported as a decimal or fraction. c. A value near 0 means that the event is not likely to occur/happens d. It is the selection of several experiments 5. Which of the following is not a condition of the binomial distribution? a. Only 2 possible outcomes b. Have constant probability of success c. Must have atleast 3 trials d. Trials must be independent 6. The joint probability is a. The likelihood of two events happening together

b. Based on 2 mutually exclusive events c. Also called priori probability d. The likelihood of an event happening given that another event has already happened 7. In special rule of addition of probability, the events are always a. Independent b. Mutually exclusive c. Bayesian d. Empirical 8. If the occurrence of one event means that another cannot happen, then the events are a. Bayesian b. Empirical c. Mutually exclusive d. Independent 9. 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? a. 4/36 b. 13/36 c. 21/36 d.15/36 10. The special rule of multiplication of probability, the events must be a. Empirical b. Independent c. Mutually exclusive d. Bayesian 11. A listing of the possible outcomes of an experiment and their corresponding probability is called a. Random variable b. Contingency table c. Bayesian table

d. Probability distribution 12. The collection of one or more outcomes from an experiment is called a. Event b. Random variable c. Probability d. Z-value 13. If a card is chosen from a standard deck of cards, what is the probability of getting a diamond (♦) or a club(♣)? a. 13/52 b.26/52 c.20/52 d.12/52 14. In a Poisson probability distribution a. The number trials is always less than 5 b. It always contains a contingency table c. The mean and variance of the distribution are same d. The probability of success is always greater than 5 15. The variance of binomial distribution is always a. Less than mean b. Equal to mean c. Greater than mean d. Equal to standard deviation 16. In binomial distribution n=6 and p=0.9, then the value of P(X=7) is a. One b. Less than zero c. Zero d. More than zero 17. Binomial distribution is negatively skewed when a. P=0

b.P>1/2 c.Pq c.pnpq 28. A random variable X has binomial distribution with n = 10 and p = 0.3 then variance of X is

a. 10 b. 12 c.2.1 d. 21 29. If in a binomial distribution n = 1 then E(X) is a. q b. p c. 0 d.1 30. If C is non-random variable, the E(C) is a. Zero b. C c.1 d.2 31. The probability function is always a. Negative b. Non-negative c. Positive d. None of the above 32. Total Area under the curve in probability of density function is a. 0 b. 1 c.-1 d.∞ 33. A discrete probability distribution may be represented by a. A table b. A graph

c. A mathematical equation d. All of the above 34. Probability distribution of a random variable is also known as a. Probability b. Probability function c. Distribution function d. Probability distribution 35. Probability of occurrence of an event lies between a. -1 and 0 b. -1 and 1 c. 0 and 1 d. Exactly 1 36. Area under the normal curve on either side of mean is a.-1 b. 0.5 c. Mean value d.1 37. The median of normal distribution corresponds to the value of Z equal to a. 0.5 b. 0 c. 1 d.µ 38. If X follows N(55,49) then σ a. 7 b. 49 c. 55 d. 104

39. The Normal Distribution has parameters a. 2 b.1 c.4 d.3 40. In a normal distribution E(X−μ)2 is a. Mean deviation b. Variance c. Standard deviation d. Quartile deviation 41. Which of the following parameter control the relative flatness of normal distribution a. Mean b. Mode c. Standard deviation d. None 42. In case of symmetrical distribution a. β1=β4 b. Mean=Median=Mode c.µ1=µ2 d.µ3=µ4 43. If Y=5X + 10 and X is N(10,25), then mean of Y is a. 70 b. 50 c. 135 d.60 44. Normal Distribution a. Uni modal

b. Bi modal c. Tri modal d. Multi modal 45. Total Area under the normal curve is a. 0 b. 1 c. Greater than 1 d. Less than 1 46. We use normal distribution when "n" is a. Small b. Fixed c. Large d. None 47. In Normal distribution, the parameters which controls the flatness of the curve is a. µ,MD b. µ,σ c. Square root of 2π,e d. None 48. If X~N(16, 49), then mean is a. 7 b. 4 c. 49 d. 16 49. The shape of normal curve depends upon a. Standard deviation b. Mean deviation c. Quartile deviation

d. None 50. Normal Distribution is a. Meso kurtic b. Lepto kurtic c. Platy kurtic d. None 51. The Normal Curve is asymptotic to the a. along Y=X b. X-axis c. Y-axis d. None 52. Mean deviation of Normal Distribution is a. 7/8σ b. 2/3σ c.3/4σ d.4/5σ 53. The lower and upper quartiles of standard normal variate are respectively a. -0.7979 and 0.7979 b. µ+0.6745σ and µ-0.6745σ c. -0.7979σ and 0.7979σ d. -0.6745 and 0.6745 54. Shape of normal curve can be related to a. Bell b. Rectangle c. Circle d. J 55. A random variable is also called as

a. Attribute b. Constant c. Variable d. Chance variable 56. Probability with out any conditions of occurrence of an event is considered as a. Conditional probability b. Marginal probability c. Occurrence probability d. Non conditional probability 57. Way of getting information from measuring observation whose outcomes occurrence is on chance is called a. Random experiment b. Beta experiment c. alpha experiment d. Gamma experiment 58. Probability of second event in situation if first event has been occurred is classified as a. Series probability b. Conditional probability c. Joint probability d. Dependent probability 59. Probability which is based on self beliefs of persons involved in experiment is classified as a. Sample approach b. Objective approach c. Intuitive approach d. Subjective approach 60. In probability theories, events which can never occur together are classified as a. Mutually exclusive b. Mutually exhaustive

c. Collectively exhaustive d. Collectively exclusive 61. Consider two events X and Y, X-bar and Y-bar represents a. Occurrence of Y b. Occurrence of X c. Nonoccurrence of X and Y d. Occurrence of X and Y 62. In measuring probability of any certain event, zero represents a. Impossible b. Possible c. Certain d. Sample 63. If a person buys a lottery, chance of winning a Toyota car is 60%, chance of winning Hyundai car is 70% and 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 64. Outcomes of an experiment are classified as a. Logged events b. Exponential results c. Results d. Events 65. For a random experiment, all possible outcomes are called a. Numerical space b. Event space c. Sample space

d. Both b and c 66. In probability theory, events are denoted by a. Greek letters b. Capital letters c. Small letters d. Latin letters 67. If a brown sack consists of 4 white balls and 3 black balls then probability of one randomly drawn ball will be white is a. 4/7 b. 1/7 c. 4/4 d. 4/3 68. Method in which previously calculated probabilities are revised with new probabilities is classified as a. Updating theorem b. Revised theorem c. Baye’s theorem d. Dependent theorem 69. Measure of chance of an uncertain event in form of numerical figures is classified as a. Probability b. Variability c. Durability d. Likelihood 70. For mutually exclusive events, 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 71. 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) 72. Probability of 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) 73. Method of counting outcomes in which number of outcomes are determined without prior listing is classified as a. Single experiments b. Multiple experiments c. Zero experiments d. Unlisted experiments 74. Previous probabilities in Bayes Theorem that are changed with help of new available information are classified as a. Independent probabilities b. Posterior probabilities c. Interior probabilities d. Dependent probabilities 75. Conditional probability of two events Y and Z written as P(Z|Y) = P(Y and Z) ⁄ P(A) shows that events are a. Statistically dependent b. Descriptive unaffected c. Statistically independent

d. Statistically unaffected 76. Number of favorable occurrences are divided by total number of possible occurrences to calculate a. Probability of an event b. Total outcomes of an event c. Sample space of experiment d. None of the above 77. If occurrence of one event does not affects or explains occurrence of other event then events are classified as a. Dependent b. Known c. Independent d. Unknown 78. If occurrence of one event affects or explains occurrence of other event then events are classified as a. Dependent b. Known c. Unknown d. Independent...