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Set Theoretical Notations of Probability - Practice Questions & MCQ

Edited By admin | Updated on Sep 18, 2023 18:34 AM | #JEE Main

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  • Set Theoretical Notations of Probability is considered one of the most asked concept.

  • 48 Questions around this concept.

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For three events A, B, and C, P(Exactly one of A or B occurs) =P(Exactly one of B or C occurs)
=P(Exactly one of C or A occurs)  =\frac{1}{4}   and P(All three events occur simultaneously)  =\frac{1}{16}. Then the probability that at least one of the events occurs, is :

 A number x is chosen at random from the set {1,2,3,4........100} Define the event : A= the chosen number x satisfies

\frac{\left ( x-10 \right )\left ( x-50 \right )}{\left ( x-30 \right )}\geqslant 0 Then P(A) is :

In a class of 60 students, 40 opted for NCC, 30 opted for NSS and 20 opted for both NCC and NSS. If one of these students is selected at random, then the probability that the student selected has opted neither for NCC nor for NSS is :

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Two dice are thrown. What is the probability that the sum of the numbers on the two dice is eight?

In a class of 200 students, 125 students have taken a programming language course, 85 students have taken a data structures course, 65 students have taken a computer organization course, 50 students have taken both programming languages and data: structures, 35 students have taken both programming languages and computing organization, 30 students have taken both data structures and computer organization, 15 students have taken all the three courses. How many students have not taken any of the three courses?

If M and N are any two events, the probability that at least one of them occurs is

In a town of 840 persons, 450 persons read Hindi, 300 read English and 200 read both. Then the number of persons who read neither is

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A bag contains $5$ Red and $3$ Blue balls. If $3$ balls are drawn at random without replacement, the probability of getting exactly one Red ball.

Which of the following does not represent the probability of occurrence of exactly one of A and B.

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A board has 16 squares as shown in the figure :

Out of these 16 squares, two squares are chosen at random. The probability that they have no side in common is :

Concepts Covered - 1

Set Theoretical Notations of Probability

The Addition Rule of Probability 

(Probability of the event ‘A or B’ )

If $A$ and $B$ are any two events defined on a sample space, then the probability of occurrence of at least one of the event $A$ and $B$ is $P(A \cup B)$ and it equals $P(A)+P(B)-P(A \cap B)$.
From the set theory, we know that

$
n(A \cup B)=n(A)+n(B)-n(A \cap B)
$
Divide by $n(S)$ both side

$
\begin{aligned}
& \frac{n(A \cup B)}{n(S)}=\frac{n(A)}{n(S)}+\frac{n(B)}{n(S)}-\frac{n(A \cap B)}{n(S)} \\
& P(A \cup B)=P(A)+P(B)-P(A \cap B)
\end{aligned}
$

  

Special case

If $A$ and $B$ are disjoint sets, i.e., they are mutually exclusive events, then $A \cap B=\varphi$. Therefore $P(A \cap B)=P(\varphi)$ $=0$

Thus, for mutually exclusive events $A$ and $B$, we have $P(A \cup B)=P(A)+P(B)$

If $A$ and $B$ are two events, then

$
(A-B) \cap(A \cap B)=\varphi \quad \text { and } \quad A=(A-B) \cup(A \cap B)
$

$
\begin{aligned}
& \text { So, } P(A)=P(A-B)+P(A \cap B)-0 \\
& =P\left(A \cap B^{\prime}\right)+P(A \cap B)
\end{aligned}
$

or $P(A)-P(A \cap B)=P\left(A \cap B^{\prime}\right)=P(A-B)$

$
\left[\because A-B=A \cap B^{\prime}\right]
$
Similarly, $P(B)-P(A \cap B)=P\left(B \cap A^{\prime}\right)=P(B-A)$
If $A, B$ and $C$ are any three events in a sample space $S$, then

$
P(A \cup B \cup C)=P(A)+P(B)+P(C)-P(A \cap B)-P(A \cap C)-P(B \cap C)+P(A \cap B \cap C
$

If $\mathrm{A}, \mathrm{B}$ and C are any three mutually exclusive events in a sample space S , then $P(A \cup B \cup C)=P(A)+P(B)+P(C)$

  

Probability of event ‘not A’ or Complementary Event

If E is the any event and $\mathrm{E}^{\prime}$ be the complement of the event E . Since, E and $\mathrm{E}^{\prime}$ are disjoint and exhaustive sets.
\begin{array}{ll} 
& \mathrm{E} \cup \mathrm{E}^{\prime}=\mathrm{S} \\
\therefore & \mathrm{n}\left(\mathrm{E} \cup \mathrm{E}^{\prime}\right)=\mathrm{n}(\mathrm{~S}) \\
\Rightarrow & \mathrm{n}(\mathrm{E})+\mathrm{n}\left(\mathrm{E}^{\prime}\right)=\mathrm{n}(\mathrm{~S}) \\
\Rightarrow & \frac{\mathrm{n}(\mathrm{E})}{\mathrm{n}(\mathrm{~S})}+\frac{\mathrm{n}\left(\mathrm{E}^{\prime}\right)}{\mathrm{n}(\mathrm{~S})}=1 \\
\Rightarrow & \mathrm{P}(\mathrm{E})+\mathrm{P}\left(\mathrm{E}^{\prime}\right)=1 \\
\Rightarrow & \mathrm{P}(\mathrm{E})=1-\mathrm{P}(\text { not } \mathrm{E})=1-\mathrm{P}\left(\mathrm{E}^{\prime}\right)
\end{array}
    

 

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Set Theoretical Notations of Probability

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