MCQOPTIONS
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MCQOPTIONS
This section includes 992 Mcqs, each offering curated multiple-choice questions to sharpen your General Aptitude knowledge and support exam preparation. Choose a topic below to get started.
| 401. |
Find the number of blue balls in the bag. |
| A. | 27 |
| B. | 26 |
| C. | 20 |
| D. | none of these |
| E. | cannot be determined |
| Answer» D. none of these | |
| 402. |
A bag contains 20 books out of which 5 are defective. If 3 of the books are selected at random and removed from the bag in succession without replacement, then what is the probability that all three books are defective? |
| A. | 0.009 |
| B. | 0.016 |
| C. | 0.026 |
| D. | 0.047 |
| Answer» B. 0.016 | |
| 403. |
A card is drawn from a well-shuffled ordinary deck of 52 cards. What is the probability that it is an ace? |
| A. | \(\frac{1}{{13}}\) |
| B. | \(\frac{2}{{13}}\) |
| C. | \(\frac{3}{{13}}\) |
| D. | \(\frac{1}{{52}}\) |
| Answer» B. \(\frac{2}{{13}}\) | |
| 404. |
A dice is thrown once. Find the probability of getting an even prime number? |
| A. | 1/2 |
| B. | 1/3 |
| C. | 1/6 |
| D. | 2/5 |
| Answer» D. 2/5 | |
| 405. |
A bag contains 4 white and 2 black balls and another bag contains 3 of each colour. A bag is selected at random and a ball is drawn at random from the bag chosen. The probability of the white ball drawn is |
| A. | \(\frac{1}{3}\) |
| B. | \(\frac{1}{4}\) |
| C. | \(\frac{5}{{12}}\) |
| D. | \(\frac{7}{{12}}\) |
| Answer» E. | |
| 406. |
A bag contains 3 blue, 2 white and 4 red balls. If a ball is drawn at random from the box, what is the probability of getting a blue ball? |
| A. | 2/3 |
| B. | 4/9 |
| C. | 1/3 |
| D. | 2/9 |
| Answer» D. 2/9 | |
| 407. |
In a group of 10 boys, 2 of them are all-rounders. What is the probability that a boy selected at random turns out to be an all-rounder? |
| A. | 5 |
| B. | 0.2 |
| C. | 0.25 |
| D. | 0.5 |
| Answer» C. 0.25 | |
| 408. |
A box contains 10 screw, 3 of which are defective. Two screws are drawn at random without replacement. The probability that none of the two screw will be defective |
| A. | 100% |
| B. | 50% |
| C. | 49% |
| D. | 47% |
| Answer» E. | |
| 409. |
Let A and B be two events such that ?\(P(\overline{A\cup B}) = \dfrac{1}{6}, P(A\cap B) = \dfrac{1}{4} \ \text{and} \ P(̅{A}) = \dfrac{1}{4}\) where A̅ stands for complement of event A. Then the events A and B are |
| A. | independent but not equally likely |
| B. | mutually exclusive and independent |
| C. | equally likely and mutually excllisive |
| D. | equally likely but not independent |
| Answer» B. mutually exclusive and independent | |
| 410. |
In march, One person is choose random from office P and placed in office Q. Then one person is transferred at random from office Q to office P. If one person is now choosen at random from office P, find the probability that he was male. |
| A. | 32/65 |
| B. | 22/57 |
| C. | 23/55 |
| D. | 56/65 |
| E. | 32/55 |
| Answer» F. | |
| 411. |
A player rolls a die and receives the same number of rupees as the number of dots on the face that turns up. What should the player pay for each roll if he wants to make a profit of one rupee per throw of the die in the long run? |
| A. | Rs. 2.50 |
| B. | Rs. 2 |
| C. | Rs. 3.50 |
| D. | Rs. 4 |
| Answer» B. Rs. 2 | |
| 412. |
If mean and variance of a Binomial variate X are 2 and 1 respectively, then the probability that X takes a value greater than 1 is |
| A. | \(\frac{2}{3}\) |
| B. | \(\frac{4}{5}\) |
| C. | \(\frac{7}{8}\) |
| D. | \(\frac{11}{16}\) |
| Answer» E. | |
| 413. |
A bag contains 4 red and some black balls. A ball is picked from the bag at random. If the probability of it being a black ball is twice that of a red ball, then the number of black balls in that bag is: |
| A. | 4 |
| B. | 8 |
| C. | 12 |
| D. | 16 |
| Answer» C. 12 | |
| 414. |
A card is drawn from a pack of well shuffled 52 playing cards. The probability that the card is black and queen is: |
| A. | 7/13 |
| B. | 1/26 |
| C. | 1/9 |
| D. | 1/13 |
| Answer» C. 1/9 | |
| 415. |
Assume that each child born is equally likely to be a boy or a girl. If two families have two children each, then the conditional probability that all children are girls given that at least two are girls is: |
| A. | 1/11 |
| B. | 1/10 |
| C. | 1/12 |
| D. | 1/17 |
| Answer» B. 1/10 | |
| 416. |
If P(E) = 0.45 then probability of 'not E' is |
| A. | 0.6 |
| B. | 0.55 |
| C. | 0.5 |
| D. | 1 |
| Answer» C. 0.5 | |
| 417. |
A box has 2 Maja, 1 Fanta, 4 Appi and 3 pepsi. If two of them are picked up one after another randomly and others are not kept in place of them, then what is the probability of that both being Appi? |
| A. | 2/3 |
| B. | 3/11 |
| C. | 2/15 |
| D. | 3/4 |
| Answer» D. 3/4 | |
| 418. |
Five sticks of length 1, 3, 5, 7 and 9 feet are given. Three of these sticks are selection at random. What is the probability that the selected sticks can form a triangle? |
| A. | 0.5 |
| B. | 0.4 |
| C. | 0.3 |
| D. | 0 |
| Answer» D. 0 | |
| 419. |
A box contains 3 black and 4 red balls. Another box contains 2 black and 3 red balls. Balls are taken from these boxes, mixed and kept in a third box. Now two balls are chosen from the third box at random. What is the probability that one of them is black and the other red? |
| A. | \(\frac{5}{{48}}\) |
| B. | \(\frac{35}{{66}}\) |
| C. | \(\frac{35}{{144}}\) |
| D. | \(\frac{5}{{66}}\) |
| Answer» C. \(\frac{35}{{144}}\) | |
| 420. |
If X is a Poisson random variate with mean 3, then P{|X - 3| < 1} will be |
| A. | \(\left( {\frac{{99}}{8}} \right){e^{ - 3}}\) |
| B. | \(\left( {\frac{{9}}{2}} \right){e^{ - 3}}\) |
| C. | \(\left( {\frac{{3}}{2}} \right){e^{ - 3}}\) |
| D. | \(\left( {\frac{{1}}{3}} \right){e^{ - 3}}\) |
| Answer» C. \(\left( {\frac{{3}}{2}} \right){e^{ - 3}}\) | |
| 421. |
A ratio of the 5th term from the beginning to the 5th term from the end in the binomial expansion of \({\left( {{2^{\frac{1}{3}}} + \frac{1}{{2{{(3)}^{\frac{1}{3}}}}}} \right)^{10}}\) is |
| A. | \(1:2{\left( 6 \right)^{\frac{1}{3}}}\) |
| B. | 1 : 4(16)3 |
| C. | \(4{\left( {36} \right)^{\frac{1}{3}}}:1\) |
| D. | \(2{\left( {36} \right)^{\frac{1}{3}}}:1\) |
| Answer» D. \(2{\left( {36} \right)^{\frac{1}{3}}}:1\) | |
| 422. |
A letter is chosen at random from the letters of the word "TRANSISTOR". The probability that the letter chosen is a consonant is __________. |
| A. | \(\frac{3}{10}\) |
| B. | \(\frac{3}{5}\) |
| C. | \(\frac{1}{2}\) |
| D. | \(\frac{7}{10}\) |
| Answer» E. | |
| 423. |
Atal speaks the truth in 70% of the cases and George speaks the truth in 60% cases. In what percentage of cases are they likely to contradict each other in stating the same fact? |
| A. | 44% |
| B. | 45% |
| C. | 46% |
| D. | 47% |
| Answer» D. 47% | |
| 424. |
Let A, B and C be three mutually exclusive and exhaustive events associated with a random experiment. If P (B) = 1.5 P (A) and P (C) = 0.5 P (B), then P (A) is equal to |
| A. | 3/4 |
| B. | 4/13 |
| C. | 2/3 |
| D. | 1/2 |
| Answer» C. 2/3 | |
| 425. |
The selling price of product is subtracted from purchasing price of product to calculate |
| A. | profit of product |
| B. | loss of profit |
| C. | cumulative average |
| D. | weighted average |
| Answer» B. loss of profit | |
| 426. |
For the Gamma distribution, if the value of n is equal to 15 and the value of μ is 7 then the expected value for this distribution is |
| A. | 3.14 |
| B. | 2.14 |
| C. | 4.14 |
| D. | 5.14 |
| Answer» C. 4.14 | |
| 427. |
In beta distribution, the expected value of random variable x is calculated as |
| A. | E(x) = m ⁄ m - n |
| B. | E(x) = n ⁄ m + n |
| C. | E(x) = m ⁄ m + n |
| D. | E(x) = n ⁄ m * n |
| Answer» D. E(x) = n ⁄ m * n | |
| 428. |
The number of units multiply profit per unit multiply probability to calculate |
| A. | discrete profit |
| B. | expected profit |
| C. | weighted profit |
| D. | continuous profit |
| Answer» C. weighted profit | |
| 429. |
The process in which the trials are statistically independent and each trial of event has only two outcomes is classified as |
| A. | Bernoulli process |
| B. | Bayes process |
| C. | functional process |
| D. | independent limited process |
| Answer» B. Bayes process | |
| 430. |
The formula of calculating the variance for negative binomial distribution is |
| A. | rq ⁄ p² |
| B. | pq ⁄ r² |
| C. | rp ⁄ q² |
| D. | rq ⁄ p |
| Answer» B. pq ⁄ r² | |
| 431. |
In the normal distribution, the normal curve becomes more wider and more flatter because of |
| A. | small value of variance |
| B. | large value of variance |
| C. | large value of standard deviation |
| D. | small value of standard deviation |
| Answer» D. small value of standard deviation | |
| 432. |
The probability which explains x is equal to or less than particular value is classified as |
| A. | discrete probability |
| B. | cumulative probability |
| C. | marginal probability |
| D. | continuous probability |
| Answer» C. marginal probability | |
| 433. |
If the sample size is 6 and the population is 50 from which it is drawn without replacement and the elements for success are 22 then the variance of hyper geometric probability distribution is |
| A. | 1.388 |
| B. | 2.388 |
| C. | 3.388 |
| D. | 4.388 |
| Answer» B. 2.388 | |
| 434. |
The symbol λ is used to represent |
| A. | variance of Poisson distribution |
| B. | standard deviation in Poisson distribution |
| C. | mean in Poisson distribution |
| D. | mean in cumulative distribution |
| Answer» D. mean in cumulative distribution | |
| 435. |
Consider the probability distribution as standard normal, if the value of μ is 75, the value of x is 120 with the unknown standard deviation of distribution then the value of z-statistic |
| A. | will be one |
| B. | will be zero |
| C. | will be negative |
| D. | will be positive |
| Answer» E. | |
| 436. |
The type of continuous distribution in which the probability is constant is classified as |
| A. | rectangular distribution |
| B. | square distribution |
| C. | open frequency distribution |
| D. | class frequency distribution |
| Answer» B. square distribution | |
| 437. |
If the value of interval a is 4 and the value of interval b is 5 then the variance of uniform distribution is |
| A. | 6.75 |
| B. | 4.75 |
| C. | 5.75 |
| D. | 0.75 |
| Answer» B. 4.75 | |
| 438. |
If the value of x is less than μ of standard normal probability distribution then the |
| A. | z-statistic is negative |
| B. | z-statistic is positive |
| C. | f(x) will be even number |
| D. | f(x) will be prime number |
| Answer» B. z-statistic is positive | |
| 439. |
The probability distribution of discrete random variable is classified as |
| A. | probability mass function |
| B. | posterior mass function |
| C. | interior mass function |
| D. | continuous mass function |
| Answer» B. posterior mass function | |
| 440. |
The standard normal probability distribution has mean equal to 40, whereas the value of random variable x is 80 and the z-statistic is equal to 1.8 then the standard deviation of standard normal probability distribution is |
| A. | 120 |
| B. | 80 |
| C. | 40 |
| D. | 20 |
| Answer» E. | |
| 441. |
If the value of λ is 9 and value of random variable x is 5 then the value of z-score is |
| A. | −2.58 |
| B. | −1.86 |
| C. | −2.34 |
| D. | −1.34 |
| Answer» E. | |
| 442. |
The formula of calculating the expected value of random variable x of gamma distribution is as |
| A. | E(x) = n ⁄ μ |
| B. | E(x) = pq ⁄ μ |
| C. | E(x) = μ ⁄ np |
| D. | E(x) = α ⁄ μ |
| Answer» B. E(x) = pq ⁄ μ | |
| 443. |
In the classification of probability distributions, the 'Erlang distribution' is also called |
| A. | alpha distribution |
| B. | beta distribution |
| C. | gamma distribution |
| D. | exponential distribution |
| Answer» D. exponential distribution | |
| 444. |
The formula of calculating mean for the negative binomial probability distribution is |
| A. | q ⁄ p |
| B. | P ⁄ Q |
| C. | p ⁄ r |
| D. | r ⁄ p |
| Answer» E. | |
| 445. |
If the value of p is smaller or lesser than 0.5 then the binomial distribution is classified as |
| A. | skewed to right |
| B. | skewed to left |
| C. | skewed to infinity |
| D. | skewed to integers |
| Answer» B. skewed to left | |
| 446. |
The mean of binomial probability distribution is 857.6 and the probability is 64% then the number of values of binomial distribution |
| A. | 1040 |
| B. | 1340 |
| C. | 1240 |
| D. | 1140 |
| Answer» C. 1240 | |
| 447. |
The tail or head, the one or zero and the girl and boy are examples of |
| A. | non-functional events |
| B. | complementary events |
| C. | non complementary events |
| D. | functional events |
| Answer» C. non complementary events | |
| 448. |
The number of products manufactured in a factory in a day are 3500 and the probability that some pieces are defected is 0.55 then the mean of binomial probability distribution is |
| A. | 1925 |
| B. | 6364 |
| C. | 63.64 |
| D. | 3500 |
| Answer» B. 6364 | |
| 449. |
The distribution whose function is calculated by considering the Bernoulli trials that are infinite In number is classified as |
| A. | negative Poisson distribution |
| B. | bimodal cumulative distribution |
| C. | common probability distribution |
| D. | negative binomial probability distribution |
| Answer» E. | |
| 450. |
The formula such as mn ⁄ (m + n)² (m + n + 1) is used to calculate |
| A. | variance in exponential distribution |
| B. | variance in alpha distribution |
| C. | variance in gamma distribution |
| D. | variance in beta distribution |
| Answer» E. | |