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NCERT Exemplar · Class 11 · Maths

Chapter 16: Probability

Practice each question, then open the answer or worked solution.

Textbook exercises

43 questions
Q41Written answer

The probability of happening of an event\[A\] is \[0.5\] and that of \[B\] is \[0.3\]. If \[A\] and \[B\] are mutually exclusive events, then the probability of neither \[A\] nor \[B\] is ________.

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Worked solution

Ans: Given: Probability of happening of an event\[A\] is \[0.5\] and that of \[B\] is \[0.3\].

Given that,

\[{\text{P}}({\text{A}}) = 0.5,\]

\[{\text{P}}({\text{B}}) = 0.3\]

and \[{\text{P}}({\text{A}} \cap {\text{B}}) = 0\]

\[\because {\text{A}}\] and \[{\text{B}}\] are mutually exclusive events

\[{\text{P}}(\overline{{A}}  \cap \overline{{B}} ) = {\text{P}}(\overline{{{A}} \cup {\text{B}}} )\]

\[ = 1 - P(A \cup B)\]

\[ = 1 - [P(A) + P(B)]\]

Substitute the values,

\[{\text{P}}(\overline {\text{A}}  \cap \overline {\text{B}} )\]\[ = 1 - (0.5 + 0.3)\]

   = 1 - 0.8

   = 0.2

Hence, the value of the filler is \[0.2.\]

The probability of happening of an event \[A\] is \[0.5\] and that of \[B\] is \[0.3\]. If A and B are mutually exclusive events, then the probability of neither A nor B is \[0.2.\]


Q42Written answer

Match the proposed probability under Column \[{C_1}\] with the appropriate written description under column \[{C_2}\].

\[{C_1}\] Probability

\[{C_2}\] Written description

\[\left( a \right) 0.95\]

(i) An incorrect assignment

\[\left( b \right) 0.02\]

(ii) No chance of happening

\[\left( c \right) - 0.3\]

(iii) As much chance of happening as not

\[\left( d \right) 0.5\]

(iv) Very likely to happen

\[\left( e \right) 0\]

(v) Very little chance of happening

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Worked solution

Ans: \[0.95 = \] Very likely to happen, so it is close to \[1{\text{ }}.\]

\[0.02 = \] Very little chance of happening as the probability is very low.

\[ - 0.3 = \] an incorrect assignment because probability is never negative.

\[0.5 = \] as much chance of happening as not because sum of chances of happening and not happening is one.

\[0 = \] no chance of happening.

Hence,

(a)$\leftrightarrow (iv),$

(b) $\leftrightarrow (v),$

(c) $\leftrightarrow (i),$

(d) $\leftrightarrow (iii),$

(e) $\leftrightarrow (ii)$ 


Q43Written answer

Match the following

(a) If \[{E_1}\] and \[{E_2}\] are the two mutually exclusive events

(i) \[{E_1}\cap {E_2}  =  {E_1}\]

(b) If \[{E_1}\] and \[{E_2}\] are the mutually exclusive and exhaustive events

(ii) \[\left( {{E_1} - {E_2} } \right)\cup \left( {{E_1} \cup {E_2}} \right)  =  {E_1}\]

(c) If \[{E_1}\] and \[{E_2}\] have common                               

outcomes, then

(iii) \[{E_1} \cap {E_2}  =  \varphi , {E_1}\cup {E_2}  =  S\]

(d) If \[{E_1}\] and \[{E_2}\] are two events                                  

such that \[{E_1} \subset {E_2}\]

(iv) \[{E_1} \cap {E_2}  =  \varphi \]

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Worked solution

Ans:  (a) If \[{{\text{E}}_1}\] and \[{{\text{E}}_2}\] are mutually exclusive events, then \[{{\text{E}}_1} \cap {{\text{E}}_2} = \phi .\]

(b) If \[{{\text{E}}_1}\] and \[{{\text{E}}_2}\] are mutually exclusive and exhaustive events then \[{{\text{E}}_1} \cap {{\text{E}}_2} = \phi \] and \[{{\text{E}}_1} \cup {{\text{E}}_2} = {\text{S}}\]

(c) If \[{{\text{E}}_1}\] and \[{{\text{E}}_2}\] have common outcomes, then \[\left( {{E_1} - {E_2}} \right) \cup \left( {{E_1} \cap {E_2}} \right) = {E_1}\]

(d) If \[{E_1}\] and \[{E_2}\] are two events such that \[{{\text{E}}_1} \subset {{\text{E}}_2} \Rightarrow {{\text{E}}_1} \cap {{\text{E}}_2} = {{\text{E}}_1}\]

Hence,

\[{\text{}}(a) \leftrightarrow (iv),(b) \leftrightarrow (iii),(c) \leftrightarrow (ii),(d) \leftrightarrow (i)\] .


The Important Topics For Chapter 16 Probability Class 11 Maths

The important topics are described as the following:

  • Random experiment

  • Outcome

  • Sample Space

  • Event

  • Types of events

  • Impossible and Sure Events

  • Simple or Elementary Event

  • Compound Event

  • Mutually exclusive event

  • Exhaustive events

  • An axiomatic approach to probability

  • Probabilities of equally likely outcomes

  • Addition rule of probability

  • Addition rule for a mutually exclusive event