27. The Poisson distribution tends to be symmetrical if the mean value is
(a) high (b) low (c) zero (d) none
28. The curve of ____________ distribution has single peak
(a) Poisson (b) Binomial (c) Normal (d) none
29. The curve of _________ distribution is unimodal and bell shaped with the highest point
over the mean
(a) Poisson (b) Normal (c) Binomial (d) none
30. Because of the symmetry of Normal distribution the median and the mode have the ______
value as that of the mean
(a) greater (b) smaller (c) same (d) none
31. For a Normal distribution, the total area under the normal curve is
(a) 0 (b) 1 (c) 2 (d) –1
32. In Normal distribution the probability has the maximum value at the
(a) mode (b) mean (c) median (d) none
33. In Normal distribution the probability decreases gradually on either side of the mean but
never touches the axis.
(a) True (b) false (c) both (d) none
34. Whatever may be the parameter of __________ distribution, it has same shape.
(a) Normal (b) Binomial (c) Poisson (d) none
35. In Standard Normal distribution
(a) mean=1, S.D=0 (b) mean=1, S.D=1
(c) mean = 0, S.D = 1 (d) mean=0, S. D=0
36. The no. of methods for fitting the normal curve is
(a) 1 (b) 2 (c) 3 (d) 4
37. ____________ distribution is symmetrical around t = 0
(a) Normal (b) Poisson (c) Binomial (d) t
38. As the degree of freedom increases, the ________ distribution approaches the Standard
Normal distribution
(a) T (b) Binomial (c) Poisson (d) Normal
39. _________ distribution is asymptotic to the horizontal axis.
(a) Binomial (b) Normal (c) Poisson (d) t
40. ________ distribution has a greater spread than Normal distribution curve
(a) T (b) Binomial (c) Poisson (d) none
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41. In Binomial Distribution if n is infinitely large, the probability p of occurrence of event’ is
close to _______ and q is close to _________
(a) 0 , 1 (b) 1 , 0 (c) 1 , 1 (d) none
42. Poisson distribution approaches a Normal distribution as n
(a) increase infinitely (b) decrease (c) increases moderately(d) none
43. If neither p nor q is very small but n sufficiently large, the Binomial distribution is very
closely approximated by _________ distribution
(a) Poisson (b) Normal (c) t (d) none
44. For discrete random variable x, Expected value of x (i.e E(x)) is defined as the sum of
products of the different values and the corresponding probabilities.
(a) True (b) false (c) both (d) none
45. For a probability distribution, —————— is the expected value of x.
(a) median (b) mode (c) mean (d) none
46. _________ is the expected value of (x – m)2 , where m is the mean.
(a) median (b) variance (c) standard deviation (d) mode
47. The probability distribution of x is given below :
value of x : 1 0 Total
probability : p 1–p 1
Mean is equal to
(a) p (b) 1–p (c) 0 (d) 1
48. For n independent trials in Binomial distribution the sum of the powers of p and q is
always n , whatever be the no. of success.
(a) True (b) false (c) both (d) none
49. In Binomial distribution parameters are
(a) n and q (b) n and p (c) p and q (d) none
50. In Binomial distribution if n = 4 and p = 1/3 then the value of variance is
(a) 8/3 (b) 8/9 (c) 4/3 (d) none
51. In Binomial distribution if mean = 20, S.D.= 4 then q is equal to
(a) 2/5 (b) 3/8 (c) 1/5 (d) 4/5
52. If in a Binomial distribution mean = 20 , S.D.= 4 then p is equal to
(a) 2/5 (b) 3/5 (c) 1/5 (d) 4/5
53. If is a Binomial distribution mean = 20 , S.D.= 4 then n is equal to
(a) 80 (b) 100 (c) 90 (d) none
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54. Poisson distribution is a ___________ probability distribution .
(a) discrete (b) continuous (c) both (d) none
55. No. of radio- active atoms decaying in a given interval of time is an example of
(a) Binomial distribution (b) Normal distribution
(c) Poisson distribution (d) None
56. __________ distribution is sometimes known as the “distribution of rare events“.
(a) Poisson (b) Normal (c) Binomial (d) none
57. The probability that x assumes a specified value in continuous probability distribution is
(a) 1 (b) 0 (c) –1 (d) none
58. In Normal distribution mean, median and mode are
(a) equal (b) not equal (c) zero (d) none
59. In Normal distribution the quartiles are equidistant from
(a) median (b) mode (c) mean (d) none
60. In Normal distribution as the distance from the ___________ increases, the curve comes
closer and closer to the horizontal axis.
(a) median (b) mean (c) mode (d) none
61. A discrete random variable x follows uniform distribution and takes only the values 6, 8,
11, 12, 17
The probability of P( x = 8) is
(a) 1/5 (b) 3/5 (c) 2/8 (d) 3/8
62. A discrete random variable x follows uniform distribution and takes the values 6, 9, 10,
11, 13
The probability of P( x = 12) is
(a) 1/5 (b) 3/5 (c) 4/5 (d) 0
63. A discrete random variable x follows uniform distribution and takes the values 6, 8, 11,
12, 17
The probability of P(x < 12) is
(a) 3/5 (b) 4/5 (c) 1/5 (d) none
64. A discrete random variable x follows uniform distribution and takes the values 6, 8, 10,
12, 18
The probability of P( x < 12) is
(a) 1/5 (b) 4/5 (c) 3/5 (d) none
65. A discrete random variable x follows uniform distribution and takes the values 5, 7, 12,
15, 18
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The probability of P( x > 10) is
(a) 3/5 (b) 2/5 (c) 4/5 (d) none
66. The probability density function of a continuous random variable is defined as follows :
f(x) = c when –1 < x < 1 = 0 , otherwise The value of c is
(a) 1 (b) –1 (c) 1/2 (d) 0
67. A continuous random variable x has the probability density fn.f(x) = ½ –ax , 0 < x < 4
When ‘a’ is a constant. The value of ‘ a’ is
(a) 7/8 (b) 1/8 (c) 3/16 (d) none
68. A continuous random variable x follows uniform distribution with probability density
function
f(x) = ½, (4 < x < 6). Then P(4 < x < 5)
(a) 0.1 (b) 0.5 (c) 0 (d) none
69. An unbiased die is tossed 500 times.The mean of the no. of ‘Sixes’ in these 500 tosses is
(a) 50/6 (b) 500/6 (c) 5/6 (d) none
70. An unbiased die is tossed 500 times. The Standard deviation of the no. of ‘sixes’ in these
500 tossed is
(a) 50/6 (b) 500/6 (c) 5/6 (d) none
71. A random variable x follows Binomial distribution with mean 2 and variance 1.2.Then
the value of n is
(a) 8 (b) 2 (c) 5 (d) none
72. A random variable x follows Binomial distribution with mean 2 and variance 1.6 then the
value of p is
(a) 1/5 (b) 4/5 (c) 3/5 (d) none
73. “The mean of a Binomial distribution is 5 and standard deviation is 3”
(a) True (b) false (c) both (d) none
74. The expected value of a constant k is the constant
(a) k (b) k–1 (c) k+1 (d) none
75. The probability distribution whose frequency function f(x)= 1/n( x = x , x …, x ) is known
1 2, n
as
(a) Binomial distribution (b) Poisson distribution
(c) Uniform distribution (d) Normal distribution
76. Theoretical distribution is a
(a) Random distribution (b) Standard distribution
(c) Probability distribution (d) None
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77. Probability function is known as
(a) frequency function (b) continuous function
(c) discrete function (d) none
78. The no. of points obtained in a single throw of an unbiased die follow :
(a) Binomial distribution (b) Poisson distribution
(c) Uniform distribution (d) None
79. The no of points in a single throw of an unbiased die has frequency function
(a) f(x)=1/4 (b) f(x)= 1/5 (c) f(x) = 1/6 (d) none
80. In uniform distribution random variable x assumes n values with
(a) equal probability (b) unequal probability (c) zero (d) none
81. In a discrete random variable x follows uniform distribution and assumes only the values
8 , 9, 11, 15, 18, 20. Then P(x = 9) is
(a) 2/6 (b) 1/7 (c) 1/5 (d) 1/6
82. In a discrete random variable x follows uniform distribution and assumes only the values
8 , 9, 11, 15, 18, 20. Then P(x = 12) is
(a) 1/6 (b) 0 (c) 1/7 (d) none
83. In a discrete random variable x follows uniform distribution and assumes only the values
8, 9, 11, 15, 18, 20. Then P(x < 15) is
(a) 1/2 (b) 2/3 (c) 1 (d) none
84. In a discrete random variable x follows uniform distribution and assumes only the values
8 , 9, 11, 15, 18, 20. Then P (x < 15) is
(a) 2/3 (b) 1/3 (c) 1 (d) none
85. In a discrete random variable x follows uniform distribution and assumes only the values
8, 9, 11, 15, 18, 20. Then P(x > 15) is
(a) 2/3 (b) 1/3 (c) 1 (d) none
86. In a discrete random variable x follows uniform distribution and assumes only the values
8, 9, 11, 15, 18, 20. Then P(|x – 14| < 5) is
(a) 1/3 (b) 2/3 (c) 1/2 (d) 1
87. When f(x)= 1/n then mean is
(a) (n–1)/2 (b) (n+1)/2 (c) n/2 (d) none
88. In continuous probability distribution P (x < t) means
(a) Area under the probability curve to the left of the vertical line at t.
(b) Area under the probability curve to the right of the vertical line at t.
(c) both (d) none
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89. In continuous probability distribution F(x) is called.
(a) frequency distribution function (b) cumulative distribution function
(c) probability density function (d) none
90. The probability density function of a continuous random variable is
y = k(x–1), ( 1 < x < 2) then the value of the constant k is
(a) –1 (b) 1 (c) 2 (d) 0
AAAAANNNNNSSSSSWWWWWEEEEERRRRRSSSSS
1 (c) 2 (a) 3 (b) 4 (b) 5 (a)
6 (b) 7 (a) 8 (b) 9 (a) 10 (b)
11 (b) 12 (a) 13 (b) 14 (b) 15 (b)
16 (c) 17 (a) 18 (c) 19 (b) 20 (a)
21 (a) 22 (b) 23 (b) 24 (c) 25 (b)
26 (c) 27 (a) 28 (c) 29 (b) 30 (c)
31 (b) 32 (b) 33 (a) 34 (a) 35 (c)
36 (b) 37 (d) 38 (a) 39 (d) 40 (a)
41 (a) 42 (a) 43 (b) 44 (a) 45 (c)
46 (b) 47 (a) 48 (a) 49 (b) 50 (b)
51 (d) 52 (c) 53 (b) 54 (a) 55 (c)
56 (a) 57 (b) 58 (a) 59 (c) 60 (b)
61 (a) 62 (d) 63 (b) 64 (c) 65 (a)
66 (c) 67 (b) 68 (b) 69 (b) 70 (a)
71 (c) 72 (a) 73 (b) 74 (a) 75 (c)
76 (c) 77 (a) 78 (c) 79 (c) 80 (a)
81 (d) 82 (b) 83 (a) 84 (a) 85 (b)
86 (c) 87 (b) 88 (a) 89 (b) 90 (c)
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