Question (1)
A die is thrown 6 times. If ‘getting an odd number’ is a success, what is the probability of
(i) 5 successes?
(ii) at least 5 successes?
(iii) at most 5 successes?
Solution
' getting an odd number ' is success.
p = probability of success. = 3/6 = 1/2 , q = 1 - p = 1/2, n = 6.
\[P(X = x) = n{C_x}{p^x}{q^{n - x}}\]
(i) 5 success = P(X = 5 )
\[ = 6{C_5}{\left( {\frac{1}{2}} \right)^5}\left( {\frac{1}{2}} \right)\]
\[ = 6 \times \frac{1}{{32}} \times \frac{1}{2}\]
\[ = \frac{3}{{32}}\]
(ii) at least 5 success = P(X ≥ 5)
= P(X=5) + P(X=6)
\[ = 6{C_5}{\left( {\frac{1}{2}} \right)^5}{\left( {\frac{1}{2}} \right)^1} + 6{C_6}{\left( {\frac{1}{2}} \right)^6}{\left( {\frac{1}{2}} \right)^0}\]
\[ = 6 \times \frac{1}{{32}} \times \frac{1}{2} + 1 \times \frac{1}{{64}} \times 1\]
\[ = \frac{6}{{64}} + \frac{1}{{64}}\]
\[ = \frac{7}{{64}}\]
(iii) at most 5 success = P(X ≤5)
= 1 - P(6)
\[ = 1 - 6{C_6}{\left( {\frac{1}{2}} \right)^6}{\left( {\frac{1}{2}} \right)^0}\]
\[ = 1 - 1 \times \frac{1}{{64}} \times 1\]
\[ = 1 - \frac{1}{{64}}\]
\[ = \frac{{63}}{{64}}\]
Question (2)
A pair of dice is thrown 4 times. If getting a doublet is considered a success, find the
probability of two successes.
Solution
A pair of dice are thrown 4 times. n = 4
Getting a doublet is success,
p = probability of success = 6/36 = 1/6 , q = 1 - p = 5/6.
\[P(X = x) = n{C_x}{p^x}{q^{n - x}}\]
P(X=2)=
\[ = 4{C_2}{\left( {\frac{1}{6}} \right)^2}{\left( {\frac{5}{6}} \right)^2}\]
\[ = 6 \times \frac{1}{{36}} \times \frac{{25}}{{36}}\]
\[ = \frac{{25}}{{216}}\]
Question (3)
There are 5% defective items in a large bulk of items. What is the probability that a sample
of 10 items will include not more than one defective item?
Solution
There are 5% defective items in bulk of items.
p = probability of success = 0.05 = 1/20 , q = 1 - p = 19/20, n = 10
\[P(X = x) = n{C_x}{p^x}{q^{n - x}}\]
P( not more than 2 defective items)
=P(X<2)
= P(X=0) + P(X=1)
\[ = 10{C_0}{\left( {\frac{1}{{20}}} \right)^0}{\left( {\frac{{19}}{{20}}} \right)^{10}} + 10{C_1}{\left( {\frac{1}{{20}}} \right)^1}{\left( {\frac{{19}}{{20}}} \right)^9}\]
\[ = 1 \times 1 \times {\left( {\frac{{19}}{{20}}} \right)^{10}} + 10 \times \frac{1}{{20}} \times {\left( {\frac{{19}}{{20}}} \right)^9}\]
\[ = {\left( {\frac{{19}}{{20}}} \right)^9}\left[ {\frac{{19}}{{20}} + \frac{{10}}{{20}}} \right]\]
\[{\left( {\frac{{19}}{{20}}} \right)^9}\left( {\frac{{29}}{{20}}} \right)\]
\[ = \left( {\frac{{29}}{{20}}} \right){\left( {\frac{{19}}{{20}}} \right)^9}\]
Question (4)
Five cards are drawn successively with replacement from a well-shuffled deck of 52 cards.
What is the probability that
(i) all the five cards are spades?
(ii) only 3 cards are spades?
(iii) none is a spade?
Solution
Five cards are drawn from the pack of cards. n = 5
p = probability of sucess = getting a spade card.
p = 13/52 = 1/4, q = 1 - p = 3/4
By Binomial expansion,
\[P(X = x) = n{C_x}{p^x}{q^{n - x}}\]
(i) all 5 cards are of spade.
P(X = 5)
\[ = 5{C_5}{\left( {\frac{1}{4}} \right)^5}{\left( {\frac{3}{4}} \right)^0}\]
\[ = 1 \times \frac{1}{{1024}} \times 1\]
\[ = \frac{1}{{1024}}\]
(ii) only 3 cards are of spade.
P(X=3)
\[ = 5{C_3}{\left( {\frac{1}{4}} \right)^3}{\left( {\frac{3}{4}} \right)^2}\]
\[ = 10 \times \frac{1}{{64}} \times \frac{9}{{16}}\]
\[ = \frac{{45}}{{512}}\]
(iii) none is spade card
P(X=0)
\[ = 5{C_0}{\left( {\frac{1}{4}} \right)^0}{\left( {\frac{3}{4}} \right)^5}\]
\[ = 1 \times 1 \times \frac{{243}}{{1024}}\]
\[ = \frac{{243}}{{1024}}\]
Question (5)
The probability that a bulb produced by a factory will fuse after 150 days of use is 0.05. Find
the probability that out of 5 such bulbs
(i) none
(ii) not more than one
(iii) more than one
(iv) at least one
will fuse after 150 days of use.
Solution
p = probability of success = a bulb produced by a factory will fuse after 150 days of use
p = 0.05, q = 1 - p = 0.95, n = 5.
By Binomial expansion,
\[P(X = x) = n{C_x}{p^x}{q^{n - x}}\]
(i) none
P(X=0)
\[ = 5{C_0}{\left( {0.05} \right)^0}{\left( {0.95} \right)^5}\]
\[ = 1 \times 1 \times {\left( {0.95} \right)^5}\]
\[ = {\left( {0.95} \right)^5}\]
(ii) Not more than 1
= P(X ≤1)
= P(X=0)+P(X=1)
\[ = \left[ {5{C_0}{{\left( {0.05} \right)}^0}{{\left( {0.95} \right)}^5} + 5{C_1}{{\left( {0.05} \right)}^1}{{\left( {0.95} \right)}^4}} \right]\]
\[ = \left[ {{{\left( {0.95} \right)}^5} + 5\left( {0.05} \right){{\left( {0.95} \right)}^4}} \right]\]
\[ = {\left( {0.95} \right)^4}\left( {0.95 + 0.25} \right)\]
\[ = {\left( {0.95} \right)^4}\left( {1.2} \right)\]
(iii) more than 1
P(X >1)
= P(X=2)+P(X=3)+P(X=4)+P(X=5)
= 1 -[ P(X=0)+P(X=1)]
\[ = 1 - \left[ {5{C_0}{{\left( {0.05} \right)}^0}{{\left( {0.95} \right)}^5} + 5{C_1}{{\left( {0.05} \right)}^1}{{\left( {0.95} \right)}^4}} \right]\]
\[ = 1 - \left[ {{{\left( {0.95} \right)}^5} + 5\left( {0.05} \right){{\left( {0.95} \right)}^4}} \right]\]
\[ = 1 - {\left( {0.95} \right)^4}\left( {0.95 + 0.25} \right)\]
\[ = 1 - {\left( {0.95} \right)^4}\left( {1.2} \right)\]
(iv) At least 1
= P(X ≥1)
= 1 - P(X=0)
\[ = 1 - \left[ {5{C_0}{{\left( {0.05} \right)}^0}{{\left( {0.95} \right)}^5}} \right]\]
\[ = 1 - {\left( {0.95} \right)^5}\]
Question (6)
A bag consists of 10 balls each marked with one of the digits 0 to 9. If four balls are drawn
successively with replacement from the bag, what is the probability that none is marked with
the digit 0?
Solution
A ball marked with digis 0 to 9. , n = 4
p = probability of success = not getting a ball with digit 0
∴ p = 1/10, q = 1 - p = 9/10
By Binomial expansion,
\[P(X = x) = n{C_x}{p^x}{q^{n - x}}\]
None is marked with 0
P(X = 0)
\[ = \left[ {4{C_0}{{\left( {\frac{1}{{10}}} \right)}^0}{{\left( {\frac{9}{{10}}} \right)}^4}} \right]\]
\[ = 1 \times 1 \times {\left( {\frac{9}{{10}}} \right)^4}\]
\[ = {\left( {\frac{9}{{10}}} \right)^4}\]
Question (7)
In an examination, 20 questions of true-false type are asked. Suppose a student tosses a fair
coin to determine his answer to each question. If the coin falls heads, he answers ‘true’; if it
falls tails, he answers ‘false’. Find the probability that he answers at least 12 questions
correctly.
Solution
p =probability of success
= giving the correct answer to question
p = 1/2, q = 1 - p = 1/2, n = 20
At least 12 question correctly
= P(X ≥12)
= P(X=12)+P(X=13)+P(X=14) +......+P(X=20)
By Binomial expansion,
\[P(X = x) = n{C_x}{p^x}{q^{n - x}}\]
\[ = 20{C_{12}}{\left( {\frac{1}{2}} \right)^{12}}{\left( {\frac{1}{2}} \right)^8} + 20{C_{13}}{\left( {\frac{1}{2}} \right)^{13}}{\left( {\frac{1}{2}} \right)^7} + 20{C_{14}}{\left( {\frac{1}{2}} \right)^{14}}{\left( {\frac{1}{2}} \right)^6} + ............ + 20{C_{20}}{\left( {\frac{1}{2}} \right)^{20}}{\left( {\frac{1}{2}} \right)^0}\]
\[ = {\left( {\frac{1}{2}} \right)^{20}}\left[ {20{C_{12}} + 20{C_{13}} + 20{C_{14}} + ....... + 20{C_{20}}} \right]\]
Question (8)
Suppose X has a binomial distribution B (6,1/2). Show that X = 3 is the most likely outcome.
(Hint: P(X = 3) is the maximum among all P(xi), xi = 0, 1, 2, 3, 4, 5, 6)
Solution
X is the binomial with n = 6, p = 1/2, q = 1 - p = 1/2.
\[P(X = x) = n{C_x}{p^x}{q^{n - x}}\]
P(X= 0) \[ = 6{C_0}{\left( {\frac{1}{2}} \right)^0}{\left( {\frac{1}{2}} \right)^6}\]
\[ = {\left( {\frac{1}{2}} \right)^6}\]
\[ = \frac{1}{{64}}\]
P(X=1) \[ = 6{C_1}{\left( {\frac{1}{2}} \right)^1}{\left( {\frac{1}{2}} \right)^5}\]
\[ = 6 \times {\left( {\frac{1}{2}} \right)^6}\]
\[ = \frac{6}{{64}}\]
P(X = 2)\[ = 6{C_2}{\left( {\frac{1}{2}} \right)^2}{\left( {\frac{1}{2}} \right)^4}\]
\[ = 15 \times {\left( {\frac{1}{2}} \right)^6}\]
\[ = \frac{{15}}{{64}}\]
P(X = 3)\[ = 6{C_3}{\left( {\frac{1}{2}} \right)^3}{\left( {\frac{1}{2}} \right)^3}\]
\[ = 20 \times {\left( {\frac{1}{2}} \right)^6}\]
\[ = \frac{{20}}{{64}}\]
P(X = 4)\[ = 6{C_4}{\left( {\frac{1}{2}} \right)^4}{\left( {\frac{1}{2}} \right)^2}\]
\[ = 15 \times {\left( {\frac{1}{2}} \right)^6}\]
\[ = \frac{{15}}{{64}}\]
P(X = 5)\[ = 6{C_5}{\left( {\frac{1}{2}} \right)^5}{\left( {\frac{1}{2}} \right)^1}\]
\[ = 6 \times {\left( {\frac{1}{2}} \right)^6}\]
\[ = \frac{{6}}{{64}}\]
P(X = 6)\[ = 6{C_6}{\left( {\frac{1}{2}} \right)^6}{\left( {\frac{1}{2}} \right)^0}\]
\[ = 1 \times {\left( {\frac{1}{2}} \right)^6}\]
\[ = \frac{{1}}{{64}}\]
Since P(X = 3) have maximum value of probability, X = 3 is most likely outcome.
Question (9)
On a multiple choice examination with three possible answers for each of the five questions,
what is the probability that a candidate would get four or more correct answers just by
guessing?
Solution
p = probability of success
= giving correct answer by guessing = 1/3
p = 1/3, q = 1 - p = 2/3, n = 5.
\[P(X = x) = n{C_x}{p^x}{q^{n - x}}\]
P( 4 or more correct ansers)
= P(X ≥4)
= P(X = 4) + P(X = 5)
\[ = 5{C_4}{\left( {\frac{1}{3}} \right)^4}{\left( {\frac{2}{3}} \right)^1} + 5{C_5}{\left( {\frac{1}{3}} \right)^5}{\left( {\frac{2}{3}} \right)^0}\]
\[ = 5 \times \frac{1}{{81}} \times \frac{2}{3} + 1 \times \frac{1}{{243}} \times 1\]
\[ = \frac{{10 + 1}}{{243}}\]
\[ = \frac{{11}}{{243}}\]
Question (10)
A person buys a lottery ticket in 50 lotteries, in each of which his chance of winning a prize
is 1/100. What is the probability that he will win a prize
(a) at least once
(b) exactly once
(c) at least twice?
Solution
n = 50, p = probability of winning = 1/100, q = 1 - p = 99/100
\[P(X = x) = n{C_x}{p^x}{q^{n - x}}\]
(a) at least once.
P( X ≥ 1)
= 1 - P(X = 0)
\[ = 1 - 50{C_0}{\left( {\frac{1}{{100}}} \right)^0}{\left( {\frac{{99}}{{100}}} \right)^{50}}\]
\[ = 1 - {\left( {\frac{{99}}{{100}}} \right)^{50}}\]
(b) Exactly once.
P(X = 0 )
\[ = 50{C_1}{\left( {\frac{1}{{100}}} \right)^1}{\left( {\frac{{99}}{{100}}} \right)^{49}}\]
\[ = 50 \times \frac{1}{{100}} \times {\left( {\frac{{99}}{{100}}} \right)^{49}}\]
\[ = \frac{1}{2}{\left( {\frac{{99}}{{100}}} \right)^{49}}\]
(c) at least twice
P( X ≥ 2)
= 1 - [ P(X=0) + P(X=1)]
\[ = 1 - \left[ {50{C_0}{{\left( {\frac{1}{{100}}} \right)}^0}{{\left( {\frac{{99}}{{100}}} \right)}^{50}} + 50{C_1}{{\left( {\frac{1}{{100}}} \right)}^1}{{\left( {\frac{{99}}{{100}}} \right)}^{49}}} \right]\]
\[ = 1 - \left[ {1 \times 1 \times {{\left( {\frac{{99}}{{100}}} \right)}^{50}} + 50 \times \frac{1}{{100}} \times {{\left( {\frac{{99}}{{100}}} \right)}^{49}}} \right]\]
\[ = 1 - {\left( {\frac{{99}}{{100}}} \right)^{49}}\left[ {\frac{{99}}{{100}} + \frac{{50}}{{100}}} \right]\]
\[ = 1 - \frac{{149}}{{100}}{\left( {\frac{{99}}{{100}}} \right)^{49}}\]
Question (11)
. Find the probability of getting 5 exactly twice in 7 throws of a die.
Solution
A die is thrown 7 times. n = 7.
getting 5 is success, p = 1/6, q = 1 - p = 5/6.
\[P(X = x) = n{C_x}{p^x}{q^{n - x}}\]
P( exactly 2)= P(X = 2)
\[ = 7{C_2}{\left( {\frac{1}{6}} \right)^2}{\left( {\frac{5}{6}} \right)^5}\]
\[ = 21 \times \frac{1}{{36}} \times {\left( {\frac{5}{6}} \right)^5}\]
\[ = \frac{7}{{12}}{\left( {\frac{5}{6}} \right)^5}\]
Question (12)
Find the probability of throwing at most 2 sixes in 6 throws of a single die.
Solution
A die is thrown 6 times, n = 6.
getting 6 is a success, p = 1/6, q = 1 - p = 5/6.
\[P(X = x) = n{C_x}{p^x}{q^{n - x}}\]
P(At most 2 sixes.) = P(X ≤2)
P(X = 0)+P(X = 1) + P(X = 2)
\[ = 6{C_0}{\left( {\frac{1}{6}} \right)^0}{\left( {\frac{5}{6}} \right)^6} + 6{C_1}{\left( {\frac{1}{6}} \right)^1}{\left( {\frac{5}{6}} \right)^5} + 6{C_2}{\left( {\frac{1}{6}} \right)^2}{\left( {\frac{5}{6}} \right)^4}\]
\[ = {\left( {\frac{5}{6}} \right)^4}\left[ {\frac{{25}}{{36}} + \frac{{30}}{{36}} + \frac{{15}}{{36}}} \right]\]
\[ = {\left( {\frac{5}{6}} \right)^4}\left( {\frac{{70}}{{36}}} \right)\]
\[ = \frac{{35}}{{18}}{\left( {\frac{5}{6}} \right)^4}\]
Question (13)
. It is known that 10% of certain articles manufactured are defective. What is the probability
that in a random sample of 12 such articles, 9 are defective?
Solution
getting a defective is success, p = 1/10, q = 1 - p = 9/10, n = 12.
\[P(X = x) = n{C_x}{p^x}{q^{n - x}}\]
P( X = 9 )
\[ = 12{C_9}{\left( {\frac{1}{{10}}} \right)^9}{\left( {\frac{9}{{10}}} \right)^3}\]
\[ = \frac{{12 \times 11 \times 10}}{{3 \times 2}} \times \frac{1}{{{{10}^9}}} \times \frac{{{9^3}}}{{{{10}^3}}}\]
\[ = \frac{{220 \times {9^3}}}{{{{10}^{12}}}}\]
\[ = \frac{{22 \times {9^3}}}{{{{10}^{11}}}}\]
Question (14)
. In a box containing 100 bulbs, 10 are defective. The probability that out of a sample
of 5 bulbs, none is defective is
(A) 10−1
(B) (1/2)
5
(C) (9/10)
5
(D) 9/10
Solution
p = probability of defective bulb
p = 1/10, q = 1 - p = 9/10, n = 5.
\[P(X = x) = n{C_x}{p^x}{q^{n - x}}\]
P( X = 0)
\[ = 5{C_0}{\left( {\frac{1}{{10}}} \right)^0}{\left( {\frac{9}{{10}}} \right)^5}\]
\[ = 1 \times 1 \times {\left( {\frac{9}{{10}}} \right)^5}\]
\[ = {\left( {\frac{9}{{10}}} \right)^5}\]
So C is the correct answer.
Question (15)
The probability that a student is not a swimmer is 1/5. Then the probability that out of five
students, four are swimmers is
(A)\[5{C_4}{\left( {\frac{4}{5}} \right)^4}{\left( {\frac{1}{5}} \right)^1}\]
(B) \[{\left( {\frac{4}{5}} \right)^4}{\left( {\frac{1}{5}} \right)^1}\]
(C) \[5{C_1}{\left( {\frac{4}{5}} \right)^4}{\left( {\frac{1}{5}} \right)^1}\]
(D) None of these
Solution
let p = probability that student is swimmer .
probability that he is not swimmer = 1/5, so p = 4/5, q = 1 - p = 1/5, n = 5.
\[P(X = x) = n{C_x}{p^x}{q^{n - x}}\]
P( X = 4)
\[ = 5{C_4}{\left( {\frac{4}{5}} \right)^4}{\left( {\frac{1}{5}} \right)^1}\]
\[ = 5{C_1}{\left( {\frac{4}{5}} \right)^4}{\left( {\frac{1}{5}} \right)^1}\]
So A and C are the correct answers.