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The concept of probability helps the students to assess the chance of an event occurring and logically draw conclusions from statistical and numerical outcomes. Students will get acquainted with some basic theorems of probability such as multiplication theorem, addition theorem of probability, mutually exclusive and exhaustive events, conditional probability, independent events, total probability, Bayes theorem, etc. Along with these, concepts of random variables are also introduced. The NCERT solutions on probability help students in analyzing the occurrence of various real-world events and to enhance their decision-making skills by following a logical and mathematical approach.
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These are one of the best available NCERT solutions for class 12 Maths probability, compiled by best Maths experts at Careers360 and also adhere to the latest CBSE syllabus and pattern. NCERT solutions for class 12 probability will enable you in understanding all the topics comprehensively and solve the textbook exercises efficiently, thereby gaining more confidence in facing all the competitive entrance exams like JEE Main, JEE advanced, etc., that require strong understanding of mathematics, specifically probability topics and theorems.
Students who wish to access the Class 12 Maths Chapter 13 NCERT Solutions can click on the link below to download the complete solution in PDF.
NCERT Class 12 Maths Chapter 13 Probability question answers with detailed explanations are provided below.
| Probability Class 12 Question Answers Exercise: 13.1 Page number: 413-415 Total questions: 17 |
Answer:
It is given that $P(E)=0.6,P(F)=0.3$ and $p(E\cap F)=0.2,$
$P ( E | F ) = \frac{p(E\cap F)}{P(F)}= \frac{0.2}{0.3}= \frac{2}{3}$
$P ( F | E ) = \frac{p(E\cap F)}{P(E)}= \frac{0.2}{0.6}= \frac{1}{3}$
Question 2: Compute $P(A\mid B),$ if $P(B)=0.5$ and $P(A\cap B)=0.32$
Answer:
It is given that $P(B)=0.5$ and $P(A\cap B)=0.32$
$P ( A | B ) = \frac{p(A\cap B)}{P(B)}= \frac{0.32}{0.5}=0.64$
Question 3: If $P(A)=0.8,P(B)=0.5$ and $P(B\mid A)=0.4,$ find
Answer:
It is given that P(A)=0.8, P(B)=0.5 and P(B|A)=0.4
$P ( B | A ) = \frac{p(A\cap B)}{P(A)}$
$0.4 = \frac{p(A\cap B)} {0.8}$
$p(A\cap B) = 0.4 \times 0.8$
$p(A\cap B) = 0.32$
Question 3: If $P(A)=0.8,P(B)=0.5$ and $P(B\mid A)=0.4,$ find
Answer:
It is given that $P(A)=0.8,P(B)=0.5$ and $P(B\mid A)=0.4,$
$P(A\cap B)=0.32$
$P ( A | B ) = \frac{p(A\cap B)}{P(B)}$
$P ( A | B ) = \frac{0.32}{0.5}$
$P ( A | B ) = \frac{32}{50}=0.64$
Question 3: If $P(A)=0.8,P(B)=0.5$ and $P(B\mid A)=0.4,$ find
Answer:
It is given that $P(A)=0.8,P(B)=0.5$
$P(A\cap B)=0.32$
$P(A\cup B)=P(A)+P(B)-P(A\cap B)$
$P(A\cup B)=0.8+0.5-0.32$
$P(A\cup B)=1.3-0.32$
$P(A\cup B)=0.98$
Question 4: Evaluate $P(A\cup B),$ if $2P(A)=P(B)=\frac{5}{13}$ and $P(A\mid B)=\frac{2}{5}$
Answer:
Given in the question $2P(A)=P(B)=\frac{5}{13}$ and $P(A\mid B)=\frac{2}{5}$
We know that:
$P ( A | B ) = \frac{p(A\cap B)}{P(B)}$
$\frac{2}{5} = \frac{p(A\cap B)}{\frac{5}{13}}$
$\frac{2\times 5}{5\times 13} = p(A\cap B)$
$p(A\cap B)=\frac{2}{ 13}$
Use, $p(A\cup B)=p(A)+p(B)-p(A\cap B)$
$p(A\cup B)=\frac{5}{26}+\frac{5}{13}-\frac{2}{13}$
$p(A\cup B)=\frac{11}{26}$
Question 5: If $P(A)=\frac{6}{11},P(B)=\frac{5}{11}$ and $P(A\cup B)=\frac{7}{11}.$ , find
Answer:
Given in the question
$P(A)=\frac{6}{11},P(B)=\frac{5}{11}$ and $P(A\cup B)=\frac{7}{11}.$
By using the formula:
$p(A\cup B)=p(A)+p(B)-p(A\cap B)$
$\frac{7}{11}=\frac{6}{11}+\frac{5}{11}-p(A\cap B)$
$p(A\cap B)=\frac{11}{11}-\frac{7}{11}$
$p(A\cap B)=\frac{4}{11}$
Question 5: If $P(A)=\frac{6}{11},P(B)=\frac{5}{11}$ and $P(A\cup B)=\frac{7}{11},$ find
Answer:
It is given that - $P(A)=\frac{6}{11},P(B)=\frac{5}{11}$
$p(A\cap B)=\frac{4}{11}$
We know that:
$P ( A | B ) = \frac{p(A\cap B)}{P(B)}$
$P ( A | B ) = \frac{\frac{4}{11}}{\frac{5}{11}}$
$P ( A | B ) = \frac{4}{5}$
Question 5: If $P(A)=\frac{6}{11},P(B)=\frac{5}{11}$ and $P(A\cup B)=\frac{7}{11},$ find
Answer:
Given in the question-
$P(A)=\frac{6}{11},P(B)=\frac{5}{11}$ and $p(A\cap B)=\frac{4}{11}$
Use formula
$P ( B | A ) = \frac{p(A\cap B)}{P(A)}$
$P ( B | A ) = \frac{\frac{4}{11}}{\frac{6}{11}}$
$P ( B | A ) = \frac{4}{6}=\frac{2}{3}$
Question 6: A coin is tossed three times, where
(i)E : head on third toss, F: heads on first two tosses
Answer:
The sample space S when a coin is tossed three times is
S = {HHH, HHT, HTH, HTT, THH, THT, TTH, TTT}
It can be seen that the sample space (S) has 8 elements.
Total number of outcomes $=2^{3}=8$
According to the question
E: head on third toss, F: heads on first two tosses
$E=\left \{ {HHH},{TTH},{HTH},{THH} \right \}$
$F=\left \{ {HHH},{HHT} \right \}$
$E\cap F =HHH$
$P(F)=\frac{2}{8}=\frac{1}{4}$
$P(E\cap F)=\frac{1}{8}$
$P(E| F)=\frac{P(E\cap F)}{P(F)}$
$P(E| F)=\frac{\frac{1}{8}}{\frac{1}{4}}$
$P(E| F)=\frac{4}{8}=\frac{1}{2}$
Question 6: A coin is tossed three times, where
(ii)E : at least two heads ,F : at most two heads
Answer:
The sample space S when a coin is tossed three times is
S = {HHH, HHT, HTH, HTT, THH, THT, TTH, TTT}
It can be seen that the sample space (S) has 8 elements.
Total number of outcomes $=2^{3}=8$
According to the question,
E : at least two heads, F : at most two heads
$E=\left \{ {HHH},{HTH},{THH},{HHT}\right \}=4$
$F=\left \{ {HTH},{HHT},{THH},{TTT},{HTT},{TTH},{THT} \right \}=7$
$E\cap F =\left \{ {HTH},THH,HHT\right \}=3$
$P(F)=\frac{7}{8}$
$P(E\cap F)=\frac{3}{8}$
$P(E| F)=\frac{P(E\cap F)}{P(F)}$
$P(E| F)=\frac{\frac{3}{8}}{\frac{7}{8}}$
$P(E| F)=\frac{3}{7}$
Question 6: A coin is tossed three times, where
(iii)E : at most two tails ,F : at least one tail
Answer:
The sample space S when a coin is tossed three times is
S = {HHH, HHT, HTH, HTT, THH, THT, TTH, TTT}
It can be seen that the sample space (S) has 8 elements.
Total number of outcomes $=2^{3}=8$
According to the question
E: at most two tails, F: at least one tail
$E=\left \{ {HHH},{TTH},{HTH},{THH},THT,HTT,HHT \right \}=7$
$F=\left \{ {TTT},{TTH},{HTH},{THH},THT,HTT,HHT \right \}=7$
$E\cap F=\left \{ {TTH},{HTH},{THH},THT,HTT,HHT \right \}=6$
$P(F)=\frac{7}{8}$
$P(E\cap F)=\frac{6}{8}=\frac{3}{4}$
$P(E| F)=\frac{P(E\cap F)}{P(F)}$
$P(E| F)=\frac{\frac{3}{4}}{\frac{7}{8}}$
$P(E| F)=\frac{6}{7}$
Question 7: Two coins are tossed once, where
(i) E : tail appears on one coin, F : one coin shows head
Answer:
E : tail appears on one coin, F : one coin shows head
Total outcomes =4
$E=\left \{ HT,TH \right \}=2$
$F=\left \{ HT,TH \right \}=2$
$E\cap F=\left \{ HT,TH \right \}=2$
$P(F)=\frac{2}{4}=\frac{1}{2}$
$P(E\cap F)=\frac{2}{4}=\frac{1}{2}$
$P(E| F)=\frac{P(E\cap F)}{P(F)}$
$P(E| F)=\frac{\frac{1}{2}}{\frac{1}{2}}$
$P(E| F)=1$
Question 7: Two coins are tossed once, where
(ii)E : no tail appears,F : no head appears
Answer:
E : no tail appears, F : no head appears
Total outcomes =4
$\\E={HH}\\F={TT}$
$E\cap F=\phi$
$n(E\cap F)=0$
$P(F)=1$
$P(E\cap F)=\frac{0}{4}=0$
$P(E| F)=\frac{P(E\cap F)}{P(F)}$
$P(E| F)=\frac{0}{1}=0$
Question 8: A die is thrown three times,
E : 4 appears on the third toss, F : 6 and 5 appears respectively on first two tosses
Answer:
E : 4 appears on the third toss, F : 6 and 5 appears respectively on first two tosses
Total outcomes $=6^{3}=216$
$E= \{ 114,124,134,144,154,164,214,224,234,244,254,264,314,$
$324,334,344,354,364,414,424,434,454,464,514,$
$524,534,544,554,564,614,624,634,644,654,664 \}$
$n(E)=36$
$F=\left \{ 651,652,653,654,655,656 \right \}$
$n(F)=6$
$E\cap F=\left \{ 654 \right \}$
$n(E\cap F)=1$
$P(E\cap F)=\frac{1}{216}$
$P( F)=\frac{6}{216}=\frac{1}{36}$
$P(E| F)=\frac{P(E\cap F)}{P(F)}$
$P(E| F)=\frac{\frac{1}{216}}{\frac{1}{36}}$
$P(E| F)=\frac{1}{6}$
Question 9: Mother, father and son line up at random for a family picture
E : son on one end, F : father in middle
Answer:
E : son on one end, F : father in the middle
Total outcomes $=3!=3\times 2=6$
Let S be son, M be mother, and F be father.
Then we have,
$E= \left \{ SMF,SFM,FMS,MFS \right \}$
$n(E)=4$
$F=\left \{ SFM,MFS \right \}$
$n(F)=2$
$E\cap F=\left \{ SFM,MFS \right \}$
$n(E\cap F)=2$
$P(F)=\frac{2}{6}=\frac{1}{3}$
$P(E\cap F)=\frac{2}{6}=\frac{1}{3}$
$P(E| F)=\frac{P(E\cap F)}{P(F)}$
$P(E| F)=\frac{\frac{1}{3}}{\frac{1}{3}}$
$P(E| F)=1$
Question 10: A black and a red dice are rolled.
Answer:
A black and a red dice are rolled.
Total outcomes $=6^{2}=36$
Let A be the event of obtaining a sum greater than $9$ and B be the event that the black die resulted in a $5.$
$A=\left \{ 46,55,56,64,65,66 \right \}$
$n(A)=6$
$B=\left \{ 51,52,53,54,55,56 \right \}$
$n(B)=6$
$A\cap B=\left \{ 55,56 \right \}$
$n(A\cap B)=2$
$P(A\cap B)=\frac{2}{36}$
$P( B)=\frac{6}{36}$
$P(A| B)=\frac{P(A\cap B)}{P(B)}$
$P(A| B)=\frac{\frac{2}{36}}{\frac{6}{36}}=\frac{2}{6}=\frac{1}{3}$
Question 10: A black and a red dice are rolled.
Answer:
A black and a red dice are rolled.
Total outcomes $=6^{2}=36$
Let A be the event of obtaining a sum of 8 and B be the event that the red die resulted in a number less than $4$.
$A=\left \{ 26,35,53,44,62, \right \}$
$n(A)=5$
Red dice is rolled after black dice.
$B=\left \{ 11,12,13,21,22,23,31,32,33,41,42,43,51,52,53,61,62,63 \right \}$
$n(B)=18$
$A\cap B=\left \{ 53,62 \right \}$
$n(A\cap B)=2$
$P(A\cap B)=\frac{2}{36}$
$P( B)=\frac{18}{36}$
$P(A| B)=\frac{P(A\cap B)}{P(B)}$
$P(A| B)=\frac{\frac{2}{36}}{\frac{18}{36}}=\frac{2}{18}=\frac{1}{9}$
(i) $P(E\mid F)$ and $P(F\mid E)$
Answer:
A fair die is rolled.
Total oucomes $=\left \{ 1,2,3,4,5,6 \right \}=6$
$E=\left \{ 1,3,5 \right \},F\left \{ 2,3 \right \}$
$E\cap F=\left \{ 3\right \}$
$n(E\cap F)=1$
$n( F)=2$
$n( E)=3$
$P( E)=\frac{3}{6}$ $P( F)=\frac{2}{6}$ and $P(E\cap F)=\frac{1}{6}$
$P(E| F)=\frac{P(E\cap F)}{P(F)}$
$P(E| F)=\frac{\frac{1}{6}}{\frac{2}{6}}$
$P(E| F)=\frac{1}{2}$
$P(F| E)=\frac{P(F\cap E)}{P(E)}$
$P(F| E)=\frac{\frac{1}{6}}{\frac{3}{6}}$
$P(F| E)=\frac{1}{3}$
(ii) $P(E\mid G)$ and $P(G\mid E)$
Answer:
A fair die is rolled.
Total outcomes $=\left \{ 1,2,3,4,5,6 \right \}=6$
$E=\left \{ 1,3,5 \right \}$ , $G=\left \{ 2,3,4,5 \right \}$
$E\cap G=\left \{ 3,5\right \}$
$n(E\cap G)=2$
$n( G)=4$
$n( E)=3$
$P( E)=\frac{3}{6}$ $P( G)=\frac{4}{6}$ $P(E\cap F)=\frac{2}{6}$
$P(E| G)=\frac{P(E\cap G)}{P(G)}$
$P(E| G)=\frac{\frac{2}{6}}{\frac{4}{6}}$
$P(E| G)=\frac{2}{4}=\frac{1}{2}$
$P(G| E)=\frac{P(G\cap E)}{P(E)}$
$P(G| E)=\frac{\frac{2}{6}}{\frac{3}{6}}$
$P(G| E)=\frac{2}{3}$
(iii) $P((E\cup F)\mid G)$ and $P((E\cap F)\mid G)$
Answer:
A fair die is rolled.
Total outcomes $=\left \{ 1,2,3,4,5,6 \right \}=6$
$E=\left \{ 1,3,5 \right \},F\left \{ 2,3 \right \}$ and $G=\left \{ 2,3,4,5 \right \}$
$E\cap G=\left \{ 3,5 \right \}$ , $F\cap G=\left \{ 2,3\right \}$
$(E\cap G)\cap G =\left \{ 3 \right \}$
$P[(E\cap G)\cap G] =\frac{1}{6}$ $P(E\cap G) =\frac{2}{6}$ $P(F\cap G) =\frac{2}{6}$
$P((E\cup F)|G) = P(E|G)+P(F|G) - P[(E\cap F)|G]$
$=\frac{P(E\cap G)}{P(G)}+\frac{P(F\cap G)}{P(G)}-\frac{P((E\cap F)\cap G)}{P(G)}$
$=\frac{\frac{2}{6}}{\frac{4}{6}}+\frac{\frac{2}{6}}{\frac{4}{6}}-\frac{\frac{1}{6}}{\frac{4}{6}}$
$=\frac{2}{4}+\frac{2}{4}-\frac{1}{4}$
$=\frac{3}{4}$
$P((E\cap F)|G)=\frac{P((E\cap F)\cap G)}{P(G)}$
$P((E\cap F)|G)=\frac{\frac{1}{6}}{\frac{4}{6}}$
$P((E\cap F)|G)=\frac{1}{4}$
Answer:
Assume that each born child is equally likely to be a boy or a girl.
Let first and second girl are denoted by $G_1\, \, \, and \, \, \,G_2$ respectively also first and second boy are denoted by $B_1\, \, \, and \, \, \,B_2$
If a family has two children, then total outcomes $=2^{2}=4$ $=\left \{ (B_1B_2),(G_1G_2),(G_1B_2),(G_2B_1)\right \}$
Let A= both are girls $=\left \{(G_1G_2)\right \}$
and B= the youngest is a girl = $=\left \{(G_1G_2),(B_1G_2)\right \}$
$A\cap B=\left \{(G_1G_2)\right \}$
$P(A\cap B)=\frac{1}{4}$ $P( B)=\frac{2}{4}$
$P(A| B)=\frac{P(A\cap B)}{P(B)}$
$P(A| B)=\frac{\frac{1}{4}}{\frac{2}{4}}$
$P(A| B)=\frac{1}{2}$
Therefore, the required probability is $\frac12$.
Question 12: Assume that each born child is equally likely to be a boy or a girl. If a family has two children, what is the conditional probability that both are girls given that
Answer:
Assume that each born child is equally likely to be a boy or a girl.
Let first and second girl are denoted by $G_1\, \, \, and \, \, \,G_2$ respectively also first and second boy are denoted by $B_1\, \, \, and \, \, \,B_2$
If a family has two children, then total outcomes $=2^{2}=4$ $=\left \{ (B_1B_2),(G_1G_2),(G_1B_2),(G_2B_1)\right \}$
Let A= both are girls $=\left \{(G_1G_2)\right \}$
and C= at least one is a girl = $=\left \{(G_1G_2),(B_1G_2),(G_1B_2)\right \}$
$A\cap B=\left \{(G_1G_2)\right \}$
$P(A\cap B)=\frac{1}{4}$ $P( C)=\frac{3}{4}$
$P(A| C)=\frac{P(A\cap C)}{P(C)}$
$P(A| C)=\frac{\frac{1}{4}}{\frac{3}{4}}$
$P(A| C)=\frac{1}{3}$
Answer:
An instructor has a question bank consisting of 300 easy True / False questions, 200 difficult True / False questions, 500 easy multiple choice questions and 400 difficult multiple choice questions.
Total number of questions $=300+200+500+400=1400$
Let A = question be easy.
$n(A)= 300+500=800$
$P(A)=\frac{800}{1400}=\frac{8}{14}$
Let B = multiple-choice question
$n(B)=500+400=900$
$P(B)=\frac{900}{1400}=\frac{9}{14}$
$A\cap B =$ easy multiple questions
$n(A\cap B) =500$
$P(A\cap B) =\frac{500}{1400}=\frac{5}{14}$
$P(A| B)=\frac{P(A\cap B)}{P(B)}$
$P(A| B)=\frac{\frac{5}{14}}{\frac{9}{14}}$
$P(A| B)=\frac{5}{9}$
Therefore, the required probability is $\frac 59$.
Answer:
Two dice are thrown.
Total outcomes $=6^2=36$
Let A be the event ‘the sum of numbers on the dice is 4.
$A=\left \{ (13),\left ( 22 \right ),(31) \right \}$
Let B be the event that the two numbers appearing when throwing two dice are different.
$B=\left \{ (12),(13),(14),(15),(16),(21)\left ( 23 \right ),(24),(25),(26,)(31),(32),(34),(35),(36),(41),(42),(43),(45),(46),(51),(52),(53),(54),(56) ,(61),(62),(63),(64),(65)\right \}$ $n(B)=30$
$P(B)=\frac{30}{36}$
$A\cap B=\left \{ (13),(31) \right \}$
$n(A\cap B)=2$
$P(A\cap B)=\frac{2}{36}$
$P(A| B)=\frac{P(A\cap B)}{P(B)}$
$P(A| B)=\frac{\frac{2}{36}}{\frac{30}{36}}$
$P(A| B)=\frac{2}{30}=\frac{1}{15}$
Therefore, the required probability is $\frac{1}{15}$.
Answer:
Consider the experiment of throwing a die. If a multiple of 3 comes up, throw the die again; if any other number comes up, toss a coin.
Total outcomes
$=\left \{ (1H),(1T),(2H),(2T),(31),(32),(33),(34),(35),(36),(4H),(4T),(5H),(5T),(61),(62),(63),(64),(65),(66)\right \}$
Total number of outcomes =20
Let A be an event when the coin shows a tail.
$A=\left \{ ((1T),(2T),(4T),(5T)\right \}$
Let B be an event that at least one die shows a 3.
$B=\left \{ (31),(32),(33),(34),(35),(36),(63)\right \}$
$n(B)=7$
$P(B)=\frac{7}{20}$
$A\cap B= \phi$
$n(A\cap B)= 0$
$P(A\cap B)= \frac{0}{20}=0$
$P(A| B)=\frac{P(A\cap B)}{P(B)}$
$P(A| B)=\frac{0}{\frac{7}{20}}$
$P(A| B)=0$
Question 16: In the following Exercise 16, choose the correct answer:
If $P(A)=\frac{1}{2},P(B)=0,$ then $P(A\mid B)$ is
Answer:
It is given that
$P(A)=\frac{1}{2},P(B)=0,$
$P(A| B)=\frac{P(A\cap B)}{P(B)}$
$P(A| B)=\frac{P(A\cap B)}{0}$
Hence, $P(A| B)$ is not defined.
Thus, the correct option is C.
Question 17: In the following Exercise 17, choose the correct answer:
If $A$ and $B$ are events such that $P(A\mid B)=P(B\mid A),$ then
(A) $A\subset B$ but $A\neq B$
Answer:
It is given that $P(A\mid B)=P(B\mid A),$
$\Rightarrow$ $\frac{P(A\cap B)}{P(B)}$ $=\frac{P(A\cap B)}{P(A)}$
$\Rightarrow$ $P(A)=P(B)$
Hence, option D is correct.
| Probability Class 12 Question Answers Exercise: 13.2 Page number: 421-423 Total questions: 18 |
Question 1: If $P(A)=\frac{3}{5}$ and $P(B)=\frac{1}{5},$ find $P(A\cap B)$ if $A$ and $B$ are independent events.
Answer:
$P(A)=\frac{3}{5}$ and $P(B)=\frac{1}{5},$
Given: $A$ and $B$ are independent events.
So we have, $P(A\cap B)=P(A).P(B)$
$\Rightarrow \, \, \, \, P(A\cap B)=\frac{3}{5}\times \frac{1}{5}$
$\Rightarrow \, \, \, \, P(A\cap B)=\frac{3}{25}$
Answer:
Two cards are drawn at random and without replacement from a pack of 52 playing cards.
There are 26 black cards in a pack of 52.
Let $P(A)$ be the probability that the first card is black.
Then, we have
$P(A)= \frac{26}{52}=\frac{1}{2}$
Let $P(B)$ be the probability that the second card is black.
Then, we have
$P(B)= \frac{25}{51}$
The probability that both the cards are black $=P(A).P(B)$
$=\frac{1}{2}\times \frac{25}{51}$
$=\frac{25}{102}$
Answer:
Total oranges = 15
Good oranges = 12
Bad oranges = 3
Let $P(A)$ be the probability that the first orange is good.
The, we have
$P(A)= \frac{12}{15}=\frac{4}{5}$
Let $P(B)$ be the probability that the second orange is good.
$P(B)=\frac{11}{14}$
Let $P(C)$ be the probability that the third orange is good.
$P(C)=\frac{10}{13}$
The probability that a box will be approved for sale $=P(A).P(B).P(C)$
$=\frac{4}{5}.\frac{11}{14}.\frac{10}{13}$
$=\frac{44}{91}$
Answer:
A fair coin and an unbiased die are tossed, then the total outputs are:
$= \left \{ (H1),(H2),(H3),(H4),(H5),(H6),(T1),(T2),(T3),(T4),(T5),(T6) \right \}$
$=12$
A is the event ‘the head appears on the coin’.
Total outcomes of A are : $= \left \{ (H1),(H2),(H3),(H4),(H5),(H6) \right \}$
$P(A)=\frac{6}{12}=\frac{1}{2}$
B is the event ‘3 on the die’.
Total outcomes of B are : $= \left \{ (T3),(H3)\right \}$
$P(B)=\frac{2}{12}=\frac{1}{6}$
$\therefore A\cap B = (H3)$
$P (A\cap B) = \frac{1}{12}$
Also, $P (A\cap B) = P(A).P(B)$
$P (A\cap B) = \frac{1}{2}\times \frac{1}{6}=\frac{1}{12}$
Hence, A and B are independent events.
Answer:
Total outcomes $=\left \{ 1,2,3,4,5,6 \right \}=6$ .
$A$ is the event, ‘the number is even,’
Outcomes of A $=\left \{ 2,4,6 \right \}$
$n(A)=3.$
$P(A)=\frac{3}{6}=\frac{1}{2}$
$B$ is the event, ‘the number is red’.
Outcomes of B $=\left \{ 1,2,3 \right \}$
$n(B)=3.$
$P(B)=\frac{3}{6}=\frac{1}{2}$
$\therefore (A\cap B)=\left \{ 2 \right \}$
$n(A\cap B)=1$
$P(A\cap B)=\frac{1}{6}$
Also,
$P(A\cap B)=P(A).P(B)$
$P(A\cap B)=\frac{1}{2}\times \frac{1}{2}=\frac{1}{4}\neq \frac{1}{6}$
Thus, both events A and B are not independent.
Answer:
Given :
$P(E)=\frac{3}{5},P(F)=\frac{3}{10}$ and $P(E\cap F)=\frac{1}{5}.$
For events E and F to be independent, we need
$P(E\cap F)=P(E).P(F)$
$P(E\cap F)=\frac{3}{5}\times \frac{3}{10}=\frac{9}{50}\neq \frac{1}{5}$
Hence, E and F are not independent events.
Answer:
Given,
$P(A)=\frac{1}{2},P(A\cup B)=\frac{3}{5}$
Also, A and B are mutually exclusive means $A\cap B=\phi$.
$P(A\cup B)=P(A)+P(B)-P(A\cap B)$
$\frac{3}{5}=\frac{1}{2}+P(B)-0$
$P(B)=\frac{3}{5}-\frac{1}{2}=\frac{1}{10}$
Answer:
Given,
$P(A)=\frac{1}{2},P(A\cup B)=\frac{3}{5}$
Also, A and B are independent events, which means
$P(A\cap B) = P(A).P(B)$ . Also $P(B)=p.$
$P(A\cap B) = P(A).P(B)=\frac{p}{2}$
$P(A\cup B)=P(A)+P(B)-P(A\cap B)$
$\frac{3}{5}=\frac{1}{2}+p-\frac{p}{2}$
$\frac{p}{2}=\frac{3}{5}-\frac{1}{2}=\frac{1}{10}$
$p=\frac{2}{10}=\frac{1}{5}$
Question 8: Let A and B be independent events with $P(A)=0.3$ and $P(B)=0.4$
Find
Answer:
$P(A)=0.3$ and $P(B)=0.4$
Given: A and B are independent events
So, we have
$P(A\cap B)=P(A).P(B)$
$P(A\cap B)=0.3\times 0.4=0.12$
Question 8: Let $A$ and $B$ be independent events with $P(A)=0.3$ and $P(B)=0.4$ Find
Answer:
$P(A)=0.3$ and $P(B)=0.4$
Given: A and B are independent events
So, we have
$P(A\cap B)=P(A).P(B)$
$P(A\cap B)=0.3\times 0.4=0.12$
We have, $P(A\cup B)=P(A)+P(B)-P(A\cap B)$
$P(A\cup B)=0.3+0.4-0.12=0.58$
Question 8: Let $A$ and $B$ be independent events with $P(A)=0.3$ and $P(B)=0.4$ Find
Answer:
$P(A)=0.3$ and $P(B)=0.4$
Given: A and B are independent events
So, we have $P(A\cap B)=0.12$
$P(A|B)=\frac{P(A\cap B)}{P(B)}$
$P(A|B)=\frac{0.12}{0.4}= 0.3$
Question 8: Let A and B be independent events with $P(A)=0.3$ and $P(B)=0.4$. Find
Answer:
$P(A)=0.3$ and $P(B)=0.4$
Given: A and B are independent events
So, we have $P(A\cap B)=0.12$
$P(B|A)=\frac{P(A\cap B)}{P(A)}$
$P(B|A)=\frac{0.12}{0.3}= 0.4$
Answer:
If $A$ and $B$ are two events such that $P(A)=\frac{1}{4},P(B)=\frac{1}{2}$ and $P(A\cap B)=\frac{1}{8},$
$P(not\; A\; and\; not\; B)= P(A'\cap B')$
$P(not\; A\; and\; not\; B)= P(A\cup B)'$ use, $(P(A'\cap B')= P(A\cup B)')$
$= 1-(P(A)+P(B)-P(A\cap B))$
$= 1-(\frac{1}{4}+\frac{1}{2}-\frac{1}{8})$
$= 1-(\frac{6}{8}-\frac{1}{8})$
$= 1-\frac{5}{8}$
$= \frac{3}{8}$
Answer:
If $A$ and $B$ are two events such that $P(A)=\frac{1}{2},P(B)=\frac{7}{12}$ and $P(not \; A \; or\; not\; B)=\frac{1}{4}.$
$P(A'\cup B')=\frac{1}{4}$
$P(A\cap B)'=\frac{1}{4}$ $(A'\cup B'=(A\cap B)')$
$\Rightarrow \, \, 1-P(A\cap B)=\frac{1}{4}$
$\Rightarrow \, \, \, P(A\cap B)=1-\frac{1}{4}=\frac{3}{4}$
$Also \, \, \, P(A\cap B)=P(A).P(B)$
$P(A\cap B)=\frac{1}{2}\times \frac{7}{12}=\frac{7}{24}$
As we can see $\frac{3}{4}\neq \frac{7}{24}$
Hence, A and B are not independent.
Question 11: Given two independent events $A$ and $B$ such that $P(A)=0.3,P(B)=0.6,$ Find
Answer:
$P(A)=0.3,P(B)=0.6,$
Given two independent events $A$ and $B$.
$P(A\cap B)=P(A).P(B)$
$P(A\cap B)=0.3\times 0.6=0.18$
Also, we know $P(A \, and \, B)=P(A\cap B)=0.18$
Question 11: Given two independent events A and B such that $P(A)=0.3, P(B)=0.6,$ Find
Answer:
$P(A)=0.3,P(B)=0.6,$
Given two independent events $A$ and $B$.
$P(A \; and \; not\; B)$ $=P(A)-P(A\cap B)$
$=0.3-0.18=0.12$
Question 11: Given two independent events A and B such that $P(A)=0.3,P(B)0.6,$ Find
Answer:
$P(A)=0.3,P(B)=0.6,$
$P(A\cap B)=0.18$
$P(A\; or \; B)=P(A\cup B)$
$P(A\cup B)=P(A)+P(B)-P(A\cap B)$
$=0.3+0.6-0.18$
$=0.9-0.18$
$=0.72$
Question 11: Given two independent events $A$ and $B$ such that $P(A)=0.3,P(B)=0.6,$ Find
(iv) $P(neither\; A\; nor\; B)$
Answer:
$P(A)=0.3,P(B)=0.6,$
$P(A\cap B)=0.18$
$P(A\; or \; B)=P(A\cup B)$
$P(A\cup B)=P(A)+P(B)-P(A\cap B)$
$=0.3+0.6-0.18$
$=0.9-0.18$
$=0.72$
$P(neither\; A\; nor\; B)$ $=P(A'\cap B')$
$= P((A\cup B)')$
$=1-P(A\cup B)$
$=1-0.72$
$=0.28$
Question 12: A die is tossed thrice. Find the probability of getting an odd number at least once.
Answer:
A die is tossed thrice.
Outcomes $=\left \{ 1,2,3,4,5,6 \right \}$
Odd numbers $=\left \{ 1,3,5 \right \}$
The probability of getting an odd number on the first throw
$=\frac{3}{6}=\frac{1}{2}$
The probability of getting an even number
$=\frac{3}{6}=\frac{1}{2}$
Probability of getting an even number three times
$=\frac{1}{2}\times \frac{1}{2}\times \frac{1}{2}=\frac{1}{8}$
The probability of getting an odd number at least once
= 1 - the probability of getting an odd number in none of the throws
= 1 - probability of getting an even number three times
$=1-\frac{1}{8}$
$=\frac{7}{8}$
Answer:
Two balls are drawn at random with replacement from a box containing 10 black and 8 red balls.
Total balls =18
Black balls = 10
Red balls = 8
The probability of getting a red ball in the first draw
$=\frac{8}{18}=\frac{4}{9}$
The ball is replaced after drawing the first ball.
The probability of getting a red ball in the second draw
$=\frac{8}{18}=\frac{4}{9}$
The probability that both balls are red
$=\frac{4}{9}\times \frac{4}{9}=\frac{16}{81}$
(ii) first ball is black and second is red.
Answer:
Two balls are drawn at random with replacement from a box containing 10 black and 8 red balls.
Total balls =18
Black balls = 10
Red balls = 8
The probability of getting a black ball in the first draw
$=\frac{10}{18}=\frac{5}{9}$
The ball is replaced after drawing the first ball.
The probability of getting a red ball in the second draw
$=\frac{8}{18}=\frac{4}{9}$
The probability that the first ball is black and the second is red
$=\frac{5}{9}\times \frac{4}{9}=\frac{20}{81}$
(iii) one of them is black and other is red.
Answer:
Two balls are drawn at random with replacement from a box containing 10 black and 8 red balls.
Total balls =18
Black balls = 10
Red balls = 8
Let the first ball be black and the second ball be red.
The probability of getting a black ball in the first draw
$=\frac{10}{18}=\frac{5}{9}$
The ball is replaced after drawing the first ball.
The probability of getting a red ball in the second draw
$=\frac{8}{18}=\frac{4}{9}$
The probability that the first ball is black and the second is red
$=\frac{5}{9}\times \frac{4}{9}=\frac{20}{81}$ $...........................1$
Let the first ball be red and the second ball be black.
The probability of getting a red ball in the first draw
$=\frac{8}{18}=\frac{4}{9}$
The probability of getting a black ball in the second draw
$=\frac{10}{18}=\frac{5}{9}$
The probability that the first ball is red and the second is black
$=\frac{4}{9}\times \frac{5}{9}=\frac{20}{81}$ $...........................2$
Thus,
The probability that one of them is black and the other is red = the probability that the first ball is black and the second is red + the probability that the first ball is red and the second is black $=\frac{20}{81}+\frac{20}{81}=\frac{40}{81}$
Answer:
$P(A)=\frac{1}{2}$ and $P(B)=\frac{1}{3}$
Since the problem is solved independently by A and B,
$\therefore$ $P(A\cap B)=P(A).P(B)$
$P(A\cap B)=\frac{1}{2}\times \frac{1}{3}$
$P(A\cap B)=\frac{1}{6}$
probability that the problem is solved $= P(A\cup B)$
$P(A\cup B)=P(A)+P(B)-P(A\cap B)$
$P(A\cup B)=\frac{1}{2}+\frac{1}{3}-\frac{1}{6}$
$P(A\cup B)=\frac{5}{6}-\frac{1}{6}$
$P(A\cup B)=\frac{4}{6}=\frac{2}{3}$
(ii) exactly one of them solves the problem
Answer:
$P(A)=\frac{1}{2}$ and $P(B)=\frac{1}{3}$
$P(A')=1-P(A)$ , $P(B')=1-P(B)$
$P(A')=1-\frac{1}{2}=\frac{1}{2}$ , $P(B')=1-\frac{1}{3}=\frac{2}{3}$
probability that exactly one of them solves the problem $=P(A\cap B') + P(A'\cap B)$
probability that exactly one of them solves the problem $=P(A).P(B')+P(A')P(B)$
$=\frac{1}{2}\times \frac{2}{3}+\frac{1}{2}\times \frac{1}{3}$
$= \frac{2}{6}+\frac{1}{6}$
$= \frac{3}{6}=\frac{1}{2}$
(i) E : ‘the card drawn is a spade’
F : ‘the card drawn is an ace’
Answer:
One card is drawn at random from a well-shuffled deck of $52$ cards
Total ace = 4
total spades =13
E : ‘the card drawn is a spade
F : ‘the card drawn is an ace’
$P(E)=\frac{13}{52}=\frac{1}{4}$
$P(F)=\frac{4}{52}=\frac{1}{13}$
$E\cap F :$ a card which is spade and ace = 1
$P(E\cap F)=\frac{1}{52}$
$P(E).P(F)=\frac{1}{4}\times \frac{1}{13}=\frac{1}{52}$
$\Rightarrow P(E\cap F)=P(E).P(F)=\frac{1}{52}$
Hence, E and F are independent events.
F : ‘the card drawn is a king’
Answer:
One card is drawn at random from a well-shuffled deck of $52$ cards
Total black card = 26
total king =4
E : ‘The card drawn is black’
F : ‘The card drawn is a king’
$P(E)=\frac{26}{52}=\frac{1}{2}$
$P(F)=\frac{4}{52}=\frac{1}{13}$
$E\cap F :$ a card which is black and king = 2
$P(E\cap F)=\frac{2}{52}=\frac{1}{26}$
$P(E).P(F)=\frac{1}{2}\times \frac{1}{13}=\frac{1}{26}$
$\Rightarrow P(E\cap F)=P(E).P(F)=\frac{1}{26}$
Hence, E and F are independent events.
(iii) E : ‘the card drawn is a king or queen’
F : ‘the card drawn is a queen or jack’.
Answer:
One card is drawn at random from a well-shuffled deck of $52$ cards
Total king or queen = 8
total queen or jack = 8
E : ‘the card drawn is a king or queen’
F : ‘the card drawn is a queen or jack’.
$P(E)=\frac{8}{52}=\frac{2}{13}$
$P(F)=\frac{8}{52}=\frac{2}{13}$
$E\cap F :$ a card which is queen = 4
$P(E\cap F)=\frac{4}{52}=\frac{1}{13}$
$P(E).P(F)=\frac{2}{13}\times \frac{2}{13}=\frac{4}{169}$
$\Rightarrow P(E\cap F)\neq P(E).P(F)$
Hence, E and F are not independent events
(a) Find the probability that she reads neither Hindi nor English newspapers
Answer:
H : $60\%$ of the students read Hindi newspapers,
E : $40\%$ read an English newspaper and
$H \cap E :$ $20\%$ read both Hindi and English newspapers.
$P(H)=\frac{60}{100}=\frac{6}{10}=\frac{3}{5}$
$P(E)=\frac{40}{100}=\frac{4}{10}=\frac{2}{5}$
$P(H\cap E)=\frac{20}{100}=\frac{2}{10}=\frac{1}{5}$
The probability that she reads neither Hindi nor English newspapers $=1-P(H\cup E)$
$=1-(P(H)+P(E)-P(H\cap E))$
$=1-(\frac{3}{5}+\frac{2}{5}-\frac{1}{5})$
$=1-\frac{4}{5}$
$=\frac{1}{5}$
(b) If she reads Hindi newspaper, find the probability that she reads English newspaper.
Answer:
H : $60\%$ of the students read a Hindi newspaper,
E : $40\%$ read an English newspaper and
$H \cap E :$ $20\%$ read both Hindi and English newspapers.
$P(H)=\frac{60}{100}=\frac{6}{10}=\frac{3}{5}$
$P(E)=\frac{40}{100}=\frac{4}{10}=\frac{2}{5}$
$P(H\cap E)=\frac{20}{100}=\frac{2}{10}=\frac{1}{5}$
The probability that she reads English newspapers if she reads Hindi newspapers $=P(E|H)$
$P(E|H)=\frac{P(E\cap H)}{P(H)}$
$P(E|H)=\frac{\frac{1}{5}}{\frac{3}{5}}$
$P(E|H)=\frac{1}{3}$
(c) If she reads English newspaper, find the probability that she reads Hindi newspaper.
Answer:
H : $60\%$ of the students read Hindi newspapers,
E : $40\%$ read an English newspaper and
$H \cap E :$ $20\%$ read both Hindi and English newspapers.
$P(H)=\frac{60}{100}=\frac{6}{10}=\frac{3}{5}$
$P(E)=\frac{40}{100}=\frac{4}{10}=\frac{2}{5}$
$P(H\cap E)=\frac{20}{100}=\frac{2}{10}=\frac{1}{5}$
The probability that she reads a Hindi newspaper if she reads an English newspaper $= P(H |E)$
$P(H |E)=\frac{P(H\cap E)}{P(E)}$
$P(H |E)=\frac{\frac{1}{5}}{\frac{2}{5}}$
$P(H |E)=\frac{1}{2}$
Question 17: The probability of obtaining an even prime number on each die, when a pair of dice is rolled is
Answer:
When a pair of dice is rolled, the total outcomes $=6^2=36$
Even prime number $=\left \{ 2 \right \}$
$n(even \, \, prime\, \, number)=1$
The probability of obtaining an even prime number on each die $=P(E)$
$P(E)=\frac{1}{36}$
Option D is correct.
Question 18: Two events A and B will be independent if
(A) $A$ and $B$ are mutually exclusive
(B) $P(A'B')=\left [ 1-P(A) \right ]\left [ 1-P(B) \right ]$
Answer:
Two events A and B will be independent if
$P(A\cap B)=P(A).P(B)$
Or $P(A'\cap B')=P(A'B')=P(A').P(B')=(1-P(A)).(1-P(B))$
Option B is correct.
| Probability Class 12 Question Answers Exercise: 13.3 Page number: 431-433 Total questions: 14 |
Answer:
Black balls = 5
Red balls = 5
Total balls = 10
CASE 1 Let the red ball be drawn in the first attempt.
$P(drawing\, red\, ball)=\frac{5}{10}=\frac{1}{2}$
Now two red balls are added in urn.
Now red balls = 7, black balls = 5
Total balls = 12
$P(drawing\, red\, ball)=\frac{7}{12}$
CASE 2
Let the black ball be drawn in the first attempt.
$P(drawing\, black\, ball)=\frac{5}{10}=\frac{1}{2}$
Now two black balls are added in urn.
Now red balls = 5, black balls = 7
Total balls = 12
$P(drawing\, red\, ball)=\frac{5}{12}$
The probability that the second ball is red =
$=\frac{1}{2}\times \frac{7}{12}+\frac{1}{2}\times \frac{5}{12}$
$= \frac{7}{24}+ \frac{5}{24}$
$= \frac{12}{24}=\frac{1}{2}$
Answer:
BAG 1 : Red balls =4 Black balls=4 Total balls = 8
BAG 2 : Red balls = 2 Black balls = 6 Total balls = 8
B1 : selecting bag 1
B2 : selecting bag 2
$P(B1)=P(B2)=\frac{1}{2}$
Let R be the event of getting a red ball
$P(R|B1) = P(drawing\, \, red\, \, ball\, \, from \, first \, \, bag)= \frac{4}{8}=\frac{1}{2}$
$P(R|B2) = P(drawing\, \, red\, \, ball\, \, from \, second \, \, bag)= \frac{2}{8}=\frac{1}{4}$
Probability that the ball is drawn from the first bag,
given that it is red is $P(B1|R)$ .
Using Bayes' theorem, we have
$P(B1|R) = \frac{P(B1).P(R|B1)}{P(B1).P(R|B1)+P(B2).P(R|B2)}$
$P(B1|R) = \frac{\frac{1}{2}\times \frac{1}{2}}{\frac{1}{2}\times \frac{1}{2}+\frac{1}{2}\times \frac{1}{4}}$
$P(B1|R) =\frac{\frac{1}{4}}{\frac{1}{4}+\frac{1}{8}}$
$P(B1|R) =\frac{\frac{1}{4}}{\frac{3}{8}}$
$P(B1|R) = \frac{2}{3}$
Answer:
H : resides in a hostel
D : day scholars
A : students who attain grade A
$P(H)=\frac{60}{100}=\frac{6}{10}=\frac{3}{5}$
$P(D)=\frac{40}{100}=\frac{4}{10}=\frac{2}{5}$
$P(A|H)=\frac{30}{100}=\frac{3}{10}$
$P(A|D)=\frac{20}{100}=\frac{2}{10}= \frac{1}{5}$
By Bayes' theorem :
$P(H|A)=\frac{P(H).P(A|H)}{P(H).P(A|H)+P(D).P(A|D)}$
$P(H|A)=\frac{\frac{3}{5}\times \frac{3}{10}}{\frac{3}{5}\times \frac{3}{10}+\frac{2}{5}\times \frac{1}{5}}$
$P(H|A)=\frac{\frac{9}{50}}{\frac{9}{50}+\frac{2}{25}}$
$P(H|A)=\frac{\frac{9}{50}}{\frac{13}{50}}$
$P(H|A)=\frac{9}{13}$
Answer:
A : Student knows the answer.
B : Student, guess the answer
C : Answer is correct
$P(A)=\frac{3}{4}$ $P(B)=\frac{1}{4}$
$P(C|A)=1$
$P(C|B)=\frac{1}{4}$
By Bayes' theorem :
$P(A|C)=\frac{P(A).P(C|A)}{P(A).P(C|A)+P(B).P(C|B)}$
$P(A|C)=\frac{\frac{3}{4}\times 1}{\frac{3}{4}\times 1+\frac{1}{4}\times \frac{1}{4}}$
$=\frac{\frac{3}{4}}{\frac{3}{4}+\frac{1}{16}}$ $=\frac{\frac{3}{4}}{\frac{13}{16}}$
$P(A|C)=\frac{12}{13}$
Answer:
A: Person selected is having the disease
B: Person selected does not have the disease.
C: Blood result is positive.
$P(A)= 0.1 \%=\frac{1}{1000}=0.001$
$P(B)= 1 -P(A)=1-0.001=0.999$
$P(C|A)=99\%=0.99$
$P(C|B)=0.5\%=0.005$
By Bayes' theorem :
$P(A|C)=\frac{P(A).P(C|A)}{P(A).P(C|A)+P(B).P(C|B)}$
$=\frac{0.001\times 0.99}{0.001\times 0.99+0.999\times 0.005}$
$=\frac{0.00099}{0.00099+0.004995}$
$=\frac{0.00099}{0.005985}$ $=\frac{990}{5985}$
$=\frac{22}{133}$
Answer:
Given : A : chossing a two headed coin
B : Choosing a biased coin
C : chossing a unbiased coin
$P(A)=P(B)=P(C)=\frac{1}{3}$
D : event that the coin tossed shows a head.
$P(D|A)=1$
Biased coin that comes up heads $75\%$ of the time.
$P(D|B)=\frac{75}{100}=\frac{3}{4}$
$P(D|C)=\frac{1}{2}$
$P(B|D)=\frac{P(B).P(D|B)}{P(B).P(D|B)+P(A).P(D|A)+P(C).P(D|C)}$
$P(B|D)=\frac{\frac{1}{3}\times 1}{\frac{1}{3}\times 1+\frac{1}{3}\times \frac{3}{4}+\frac{1}{3}\times \frac{1}{2}}$
$P(B|D)=\frac{\frac{1}{3}}{\frac{1}{3}+\frac{1}{4}+\frac{1}{6}}$
$P(B|D)=\frac{\frac{1}{3}}{\frac{9}{12}}$
$P(B|D)={\frac{1\times 12}{3\times 9}}$
$P(B|D)={\frac{4}{9}}$
Answer:
Let A : scooter drivers = 2000
B : car drivers = 4000
C : truck drivers = 6000
Total drivers = 12000
$P(A)=\frac{2000}{12000}=\frac{1}{6}=0.16$
$P(B)=\frac{4000}{12000}=\frac{1}{3}=0.33$
$P(C)=\frac{6000}{12000}=\frac{1}{2}=0.5$
D : the event that a person meets with an accident.
$P(D|A)= 0.01$
$P(D|B)= 0.03$
$P(D|C)= 0.15$
$P(A|D)=\frac{P(A).P(D|A)}{P(B).P(D|B)+P(A).P(D|A)+P(C).P(D|C)}$
$P(A|D)= \frac{0.16\times 0.01}{0.16\times 0.01+0.33\times 0.03+0.5\times 0.15}$
$P(A|D)= \frac{0.0016}{0.0016+0.0099+0.075}$
$P(A|D)= \frac{0.0016}{0.0865}$
$P(A|D)= 0.019$
Answer:
A : Items produced by machine A $=60\%$
B : Items produced by machine B $=40\%$
$P(A)= \frac{60}{100}=\frac{3}{5}$
$P(B)= \frac{40}{100}=\frac{2}{5}$
X : Produced item found to be defective.
$P(X|A)= \frac{2}{100}=\frac{1}{50}$
$P(X|B)= \frac{1}{100}$
$P(B|X)= \frac{P(B).P(X|B)}{P(B).P(X|B)+P(A).P(X|A)}$
$P(B|X)= \frac{\frac{2}{5}\times \frac{1}{100}}{\frac{2}{5}\times \frac{1}{100}+\frac{3}{5}\times \frac{1}{50}}$
$P(B|X)= \frac{\frac{1}{250}}{\frac{1}{250}+\frac{3}{250}}$
$P(B|X)= \frac{\frac{1}{250}}{\frac{4}{250}}$
$P(B|X)= \frac{1}{4}$
Hence, the probability that a defective item was produced by machine $B$ =
$P(B|X)= \frac{1}{4}$ .
Answer:
A: The first group will win
B: The second group will win
$P(A)=0.6$
$P(B)=0.4$
X: Event of introducing a new product.
Probability of introducing a new product if the first group wins: $P(X|A)=0.7$
Probability of introducing a new product if the second group wins: $P(X|B)=0.3$
$P(B|X)= \frac{P(B).P(X|B)}{P(B).P(X|B)+P(A).P(X|A)}$
$p(B|X) = \frac{0.4\times 0.3}{0.4\times 0.3+0.6\times 0.7}$
$p(B|X) = \frac{0.12}{0.12+0.42}$
$p(B|X) = \frac{0.12}{0.54}$
$p(B|X) = \frac{12}{54}$
$p(B|X) = \frac{2}{9}$
Hence, the probability that the new product introduced was by the second group :
$p(B|X) = \frac{2}{9}$
Answer:
Let A: Outcome on die is 5 or 6.
B: Outcome on die is 1,2,3,4
$P(A)=\frac{2}{6}=\frac{1}{3}$
$P(B)=\frac{4}{6}=\frac{2}{3}$
X: Event of getting exactly one head.
Probability of getting exactly one head when she tosses a coin three times: $P(X|A)=\frac{3}{8}$
Probability of getting exactly one head when she tosses a coin one time: $P(X|B)=\frac{1}{2}$
$P(B|X)= \frac{P(B).P(X|B)}{P(B).P(X|B)+P(A).P(X|A)}$
$P(B|X)= \frac{\frac{2}{3}\times \frac{1}{2}}{\frac{2}{3}\times \frac{1}{2}+\frac{1}{3}\times \frac{3}{8}}$
$P(B|X)= \frac{\frac{1}{3}}{\frac{1}{3}+\frac{1}{8}}$
$P(B|X)= \frac{\frac{1}{3}}{\frac{11}{24}}$
$P(B|X)= \frac{1\times 24}{3\times 11}=\frac{8}{11}$
Hence, the probability that she threw $1,2,3$ or $4$ with the die =
$P(B|X)=\frac{8}{11}$
Answer:
Let A: time consumed by machine A $=50\%$
B: time consumed by machine B $=30\%$
C: time consumed by machine C $=20\%$
Total drivers = 12000
$P(A)=\frac{50}{100}=\frac{1}{2}$
$P(B)=\frac{30}{100}=\frac{3}{10}$
$P(C)=\frac{20}{100}=\frac{1}{5}$
D: Event of producing defective items
$P(D|A)= \frac{1}{100}$
$P(D|B)= \frac{5}{100}$
$P(D|C)= \frac{7}{100}$
$P(A|D)=\frac{P(A).P(D|A)}{P(B).P(D|B)+P(A).P(D|A)+P(C).P(D|C)}$
$P(A|D)=\frac{\frac{1}{2}\times \frac{1}{100}}{\frac{1}{2}\times \frac{1}{100}+\frac{3}{10}\times \frac{5}{100}+\frac{1}{5}\times \frac{7}{100}}$
$P(A|D)=\frac{\frac{1}{2}\times \frac{1}{100}}{\frac{1}{100} (\frac{1}{2}+\frac{3}{2}+\frac{7}{5})}$
$P(A|D)=\frac{\frac{1}{2}}{ (\frac{17}{5})}$
$P(A|D)= \frac{5}{34}$
Hence, the probability that a defective item was produced by $A$
= $P(A|D)= \frac{5}{34}$
Answer:
Let A : Event of choosing a diamond card.
B : Event of not choosing a diamond card.
$P(A)=\frac{13}{52}=\frac{1}{4}$
$P(B)=\frac{39}{52}=\frac{3}{4}$
X : The lost card.
If the lost card is a diamond, then 12 diamond cards are left out of 51 cards.
Two diamond cards are drawn out of 12 diamond cards in $^{12}\textrm{C}_2$ ways.
Similarly, two cards are drawn out of 51 cards in $^{51}\textrm{C}_2$ ways.
Probability of getting two diamond cards when one diamond is lost : $P(X|A)= \frac{^{12}\textrm{C}_2}{^{51}\textrm{C}_2}$
$P(X|A)=\frac{12!}{10!\times 2!}\times \frac{49!\times 2!}{51!}$
$P(X|A)=\frac{11\times 12}{50\times 51}$
$P(X|A)=\frac{22}{425}$
If the lost card is not a diamond, then 13 diamond cards are left out of 51 cards.
Two diamond cards are drawn out of 13 diamond cards in $^{13}\textrm{C}_2$ ways.
Similarly, two cards are drawn out of 51 cards in $^{51}\textrm{C}_2$ ways.
Probability of getting two diamond cards when one diamond is not lost : $P(X|B)= \frac{^{13}\textrm{C}_2}{^{51}\textrm{C}_2}$
$P(X|B)=\frac{13!}{11!\times 2!}\times \frac{49!\times 2!}{51!}$
$P(X|B)=\frac{13\times 12}{50\times 51}$
$P(X|B)=\frac{26}{425}$
The probability of the lost card being a diamond : $P(B|X)$
$P(B|X)= \frac{P(B).P(X|B)}{P(B).P(X|B)+P(A).P(X|A)}$
$P(B|X)= \frac{\frac{1}{4}\times \frac{22}{425}}{\frac{1}{4}\times \frac{22}{425}+\frac{3}{4}\times \frac{26}{425}}$
$P(B|X)= \frac{\frac{11}{2}}{25}$
$P(B|X)= \frac{11}{50}$
Hence, the probability of the lost card being a diamond :
$P(B|X)= \frac{11}{50}$
Answer:
Let A : A speaks truth
B : A speaks false
$P(A)=\frac{4}{5}$
$P(B)=1-\frac{4}{5}=\frac{1}{5}$
X : Event that the head appears.
A coin is tossed, the outcomes are head or tail.
Probability of getting a head whether A speaks thruth or not is $\frac{1}{2}$
$P(X|A)=P(X|B)=\frac{1}{2}$
$P(A|X)= \frac{P(A).P(X|A)}{P(B).P(X|B)+P(A).P(X|A)}$
$P(A|X)= \frac{\frac{4}{5}\times \frac{1}{2}}{\frac{4}{5}\times \frac{1}{2}+\frac{1}{5}\times \frac{1}{2}}$
$P(A|X)= \frac{\frac{4}{5}}{\frac{4}{5}+\frac{1}{5}}$
$P(A|X)= \frac{\frac{4}{5}}{\frac{1}{1}}$
$P(A|X)={\frac{4}{5}}$
The probability that actually there was head is $P(A|X)={\frac{4}{5}}$
Hence, option A is correct.
Question 14: If $A$ and $B$ are two events such that $A\subset B$ and $P(B)\neq 0,$ then which of the following is correct?
(A) $P(A\mid B)=\frac{P(B)}{P(A)}$
Answer:
If $A\subset B$ and $P(B)\neq 0,$ then
$\Rightarrow \, \, \, (A\cap B) = A$
Also, $P(A)< P(B)$
$P(A|B)=\frac{P(A\cap B)}{P(B)}=\frac{P(A)}{P(B)}$
We know that $P(B)\leq 1$
$1\leq \frac{1}{P(B)}$
$P(A)\leq \frac{P(A)}{P(B)}$
$P(A)\leq P(A|B)$
Hence, we can see that option C is correct.
| Probability Class 12 Question Answers Miscellaneous Exercise Page number: 435-437 Total questions: 13 |
Question 1(i): A and B are two events such that $P(A)\neq 0.$ Find $P(B\mid A),$ if
Answer:
A and B are two events such that $P(A)\neq 0.$
$A\subset B$
$\Rightarrow A\cap B=A$
$P(A\cap B)=P(B\cap A)=P(A)$
$P(B|A)=\frac{P(B\cap A)}{P(A)}$
$P(B|A)=\frac{P( A)}{P(A)}$
$P(B|A)=1$
Question 1(ii): $A$ and $B$ are two events such that $P(A)\neq 0.$ Find $P(B\mid A),$ if
Answer:
A and B are two events such that $P(A)\neq 0.$
$P(A\cap B)=P(B\cap A)=0$
$P(B|A)=\frac{P(B\cap A)}{P(A)}$
$P(B|A)=\frac{0}{P(A)}$
$P(B|A)=0$
Question 2 (i): A couple has two children,
Answer:
A couple has two children,
sample space $=\left \{ (b,b),(g,g),(b,g),(g,b) \right \}$
Let A be that both children are males, and B be that at least one of the children is male.
$(A\cap B)=\left \{ (b,b) \right \}$
$P(A\cap B)=\frac{1}{4}$
$P(A)=\frac{1}{4}$
$P(B)=\frac{3}{4}$
$P(A|B)=\frac{P(A\cap B)}{P(B)}$
$P(A|B)=\frac{\frac{1}{4}}{\frac{3}{4}}=\frac{1}{3}$
Question 2 (ii): A couple has two children,
Answer:
A couple has two children,
sample space $=\left \{ (b,b),(g,g),(b,g),(g,b) \right \}$
Let A be that both children are females, and B be that the elder child is a female.
$(A\cap B)=\left \{ (g,g) \right \}$
$P(A\cap B)=\frac{1}{4}$
$P(A)=\frac{1}{4}$
$P(B)=\frac{2}{4}$
$P(A|B)=\frac{P(A\cap B)}{P(B)}$
$P(A|B)=\frac{\frac{1}{4}}{\frac{2}{4}}=\frac{1}{2}$
Answer:
We have $5\%$ of men and $0.25\%$ of women have grey hair.
Percentage of people with grey hairs $=(5+0.25)\%=5.25\%$
The probability that the selected haired person is male :
$=\frac{5}{5.25}=\frac{20}{21}$
Answer:
$90\%$ of people are right-handed.
$P(right-handed)=\frac{9}{10}$
$P(left-handed)=q=1-\frac{9}{10}=\frac{1}{10}$
at most $6$ of a random sample of $10$ people are right-handed.
the probability that more than $6$ of a random sample of $10$ people are right-handed is given by,
$
\begin{aligned}
& \sum_T^{10}{ }^{10} C_r P^r q^{10-r} \\
& =\sum_T^{10}{ }^{10} C_r \frac{9}{10}{ }^r \cdot\left(\frac{1}{10}\right)^{10-r}
\end{aligned}
$
The probability that at most 6 of a random sample of 10 people are right-handed is given by
$
=1-\sum_T^{10}{ }^{10} C_r \cdot \frac{9}{10}^r \cdot\left(\frac{1}{10}^{10-r})\right.
$
Question 5: If a leap year is selected at random, what is the chance that it will contain 53 Tuesdays?
Answer:
In a leap year, there are 366 days.
In 52 weeks, there are 52 Tuesdays.
The probability that a leap year will have 53 Tuesdays is equal to the probability that the remaining 2 days are Tuesdays.
The remaining 2 days can be :
1. Monday and Tuesday
2. Tuesday and Wednesday
3. Wednesday and Thursday
4. Thursday and Friday
5. Friday and Saturday
6. Saturday and Sunday
7. Sunday and Monday
Total cases = 7.
Favorable cases = 2
Probability of having 53 Tuesdays in a leap year = P.
$P=\frac{2}{7}$
Question 6: Suppose we have four boxes A, B, C and D containing coloured marbles as given below:

(i) from box A?
(ii) from box B?
(iii) from box C?
Answer:
'
(i)
Let R be the event of drawing a red marble.
Let $E_A, E_B, E_C$ respectively denote the event of selecting box A, B, C.
Total marbles = 40
Red marbles =15
$P(R)=\frac{15}{40}=\frac{3}{8}$
Probability of drawing a red marble from box A is $P(E_A|R)$
$P(E_A|R)=\frac{P(E_A\cap R)}{P(R)}$
$=\frac{\frac{1}{40}}{\frac{3}{8}}$
$=\frac{1}{15}$
(ii)
Let R be the event of drawing a red marble.
Let $E_A, E_B, E_C$ respectively denote events of selecting box A, B, and C.
Total marbles = 40
Red marbles =15
$P(R)=\frac{15}{40}=\frac{3}{8}$
Probability of drawing a red marble from box B is $P(E_B|R)$
$P(E_B|R)=\frac{P(E_B\cap R)}{P(R)}$
$=\frac{\frac{6}{40}}{\frac{3}{8}}$
$=\frac{2}{5}$
(iii)
Let R be the event of drawing a red marble.
Let $E_A,E_B,E_C$ respectively denote the event of selecting box A, B, and C.
Total marbles = 40
Red marbles =15
$P(R)=\frac{15}{40}=\frac{3}{8}$
Probability of drawing a red marble from box C is $P(E_C|R)$
$P(E_C|R)=\frac{P(E_C\cap R)}{P(R)}$
$=\frac{\frac{8}{40}}{\frac{3}{8}}$
$=\frac{8}{15}$
Answer:
Let $A, E_1$, and $E_2$, respectively, denote the event that a person has a heartbreak, the selected person followed the course of yoga and meditation, and the person adopted the drug prescription.
$\therefore \, \, \, \, P(A)=0.40$
$\therefore \, \, \, \, P(E_1)=P(E_2)=\frac{1}{2}$
$P(A|E_1)=0.40\times 0.70=0.28$
$P(A|E_2)=0.40\times 0.75=0.30$
The probability that the patient followed a course of meditation and yoga is $P(E_1,A)$
$P(E_1,A)=\frac{P(E_1).P(E_1|A)}{P(E_1).P(E_1|A)+P(E_2).P(E_2|A)}$
$P(E_1,A)=\frac{0.5\times 0.28}{0.5\times 0.28 + 0.5\times 0.30}=\frac{14}{29}$
Answer:
Total number of determinants of the second order, with each element being 0 or 1 is $2^4=16$
The values of determinant is positive in the following cases $\begin{bmatrix} 1 & 0\\ 0 & 1\end{bmatrix}, \begin{bmatrix} 1 & 1\\ 0 & 1\end{bmatrix}, \begin{bmatrix} 1 & 0\\ 1 & 1\end{bmatrix}$
Probability is
$=\frac{3}{16}$
Evaluate the following probabilities
$P(A \; fails\mid B\; has\; failed)$
Answer:
Let the event in which A fails, and B fails be $E_A,E_B$
$P(E_A)=0.2$
$P(E_A\, and \, E_B)=0.15$
$P(B\, fails\, alone)=P(E_B)-P(E_A\, and\, E_B)$
$\Rightarrow \, \, \, 0.15=P(E_B)-0.15$
$\Rightarrow \, \, \, P(E_B)=0.3$
$P(E_A|E_B)=\frac{P(E_A\cap E_B)}{P(E_B)}$
$=\frac{0.15}{0.3}=0.5$
Evaluate the following probabilities
Answer:
Let the event in which A fails, and B fails be $E_A,E_B$
$P(E_A)=0.2$
$P(E_A\, and \, E_B)=0.15$
$P(B\, fails\, alone)=P(E_B)-P(E_A\, and\, E_B)$
$\Rightarrow \, \, \, 0.15=P(E_B)-0.15$
$\Rightarrow \, \, \, P(E_B)=0.3$
$P(A\, fails\, \, alone)=P(E_A)-P(E_A\, and\, E_B)$
$=0.2-0.15=0.05$
Answer:
Let $E_1 $ and $E_2$ respectively denote the event that a red ball is transferred from bag 1 to bag 2 and a black ball is transferred from bag 1 to bag 2.
$P(E_1)=\frac{3}{7}$ and $P(E_2)=\frac{4}{7}$
Let A be the event that the ball drawn is red.
When a red ball is transferred from bag 1 to bag 2.
$P(A|E_1)=\frac{5}{10}=\frac{1}{2}$
When a black ball is transferred from bag 1 to bag 2.
$P(A|E_2)=\frac{4}{10}=\frac{2}{5}$
$P(E_2|A)=\frac{P(E_2).P(A|E_2)}{P(E_2).P(A|E_2)+P(E_1).P(A|E_1)}$
$=\frac{\frac{4}{7}\times \frac{2}{5}}{\frac{4}{7}\times \frac{2}{5}+\frac{3}{7}\times \frac{1}{2}}$
$=\frac{16}{31}$
Question 11: If A and B are two events such that $P(A\neq 0)$ and $P(B\mid A)=1,$ then
Choose the correct answer of the following:
Answer:
A and B are two events such that $P(A\neq 0)$ and $P(B\mid A)=1,$
$P(B|A)=\frac{P(B\cap A)}{P(A)}$
$1=\frac{P(B\cap A)}{P(A)}$
$P(B\cap A)=P(A)$
$\Rightarrow \, \, \, A\subset B$
Option A is correct.
Question 12: If $P(A\mid B)> P(A)$ , then which of the following is correct :
Answer:
$P(A\mid B)> P(A)$
$\Rightarrow \, \, \frac{P(A\cap B)}{P(B)}> P(A)$
$\Rightarrow \, \, P(A\cap B)> P(A).P(B)$
$\Rightarrow \, \, \frac{P(A\cap B)}{P(A)}> P(B)$
$\Rightarrow \, \, P(B|A)> P(B)$
Option C is correct.
Question 13: If A and B are any two events such that $P(A)+P(B)-P(A \; and\; B)=P(A),$ then
Answer:
$P(A)+P(B)-P(A \; and\; B)=P(A),$
$P(A)+P(B)-P(A\cap B)=P(A)$
$\Rightarrow \, \, \, P(B)-P(A\cap B)=0$
$\Rightarrow \, \, \, P(B)=P(A\cap B)$
$P(A|B)=\frac{P(A\cap B)}{P(B)}=\frac{P(B)}{P(B)}=1$
Option B is correct.
Exercise-wise NCERT Solutions of Probability Class 12 Maths Chapter 13 are provided in the links below.
Question: Eight coins are tossed together. The probability of getting exactly 3 heads is:
Solution:
Given:
probability distribution $\mathrm{P}(\mathrm{X}=\mathrm{r})={ }^{\mathrm{n}} \mathrm{C}_{\mathrm{r}}(\mathrm{p})^r \mathrm{q}^{\mathrm{n}-\mathrm{r}}$
The total number of coins is tossed, $n=8$
The probability of getting head, $\mathrm{p}=\frac12$
The probability of getting tail, $\mathrm{q}=\frac12$
The Required probability
$
\begin{aligned}
& ={ }^8 \mathrm{C}_3\left(\frac{1}{2}\right)^3\left(\frac{1}{2}\right)^{8-3} \\
&= \frac{8 \times 7 \times 6}{3 \times 2} \times \frac{1}{2^8}=\frac{7}{32}
\end{aligned}
$
Hence, the correct answer is $\frac7{32}$.
Topics you will learn in NCERT Class 12 Maths Chapter 13 Probability include:
Conditional Probability
Conditional probability is the likelihood of an event occurring given that another event has already occurred. For two events $A$ and $B$ in the same sample space, the conditional probability of event $A$ given that $B$ has occurred, denoted by $P(A \mid B)$, is defined as:
$P(A \mid B)=\frac{P(A \cap B)}{P(B)}, \quad \text { when } P(B) \neq 0$
Other Conditional Probability Relationships
$P(S \mid F)=1 $
$P(F \mid F)=1 $
$P((A \cup B) \mid F)=P(A \mid F)+P(B \mid F)-P((A \cap B) \mid F)$
$P\left(E^{\prime} \mid F\right)=1-P(E \mid F)$
Multiplication Rule
The multiplication rule relates the probability of two events $E$ and $F$ in a sample space $S$:
$P(E \cap F)=P(E) \cdot P(F \mid E)=P(F) \cdot P(E \mid F)$
(when $P(E) \neq 0$ and $P(F) \neq 0$ )
Independent Events
Two events $E$ and $F$ are said to be independent if the occurrence of one does not affect the occurrence of the other. In such cases,
$P(E \cap F)=P(E) \cdot P(F)$
Bayes' Theorem:
Bayes' theorem deals with events $E_1, E_2, \ldots, E_n$ that form a partition of the sample space $S$. It helps in calculating the probability of an event $E_i$ given that another event $A$ has occurred.
$
P\left(E_i \mid A\right)=\frac{P\left(E_i\right) \cdot P\left(A \mid E_i\right)}{\sum_{j=1}^n P\left(E_j\right) \cdot P\left(A \mid E_j\right)}, \quad \text { for } i=1,2, \ldots, n
$
Theorem of Total Probability:
If $E_1, E_2, \ldots, E_n$ form a partition of the sample space and $A$ is any event, then the theorem of total probability states that:
$P(A)=P\left(E_1\right) \cdot P\left(A \mid E_1\right)+P\left(E_2\right) \cdot P\left(A \mid E_2\right)+\cdots+P\left(E_n\right) \cdot P\left(A \mid E_n\right)$
or, in summation form,
$P(A)=\sum_{i=1}^n P\left(E_i\right) \cdot P\left(A \mid E_i\right)$
Using these approaches, students can tackle the Probability Class 12 Chapter 13 Question Answers with greater confidence.
This chapter helps us understand how to deal with uncertain situations using mathematics. It explains how to calculate the chances of events happening and how one event can affect another. These Class 12 Maths Chapter 13 Probability question answers make these concepts easier through simple examples and clear methods. Here are some more points on why these question answers are important.
This chapter includes fundamental as well as basic application based principles of the theory of probability with the help of various arithmetic approaches. Theorem of Total Probability, Bayes' Theorem, and the concept of Random Variables are covered in this chapter. The NCERT Solutions include thorough explanations in a step-by-step manner, which simplify conceptual and numerical questions for students to grasp their concepts. With roughly 62 textbook problems spread across 4 exercises, you will be able to apply all of the ideas and strengthen your comprehension with numerical questions. Frequent practice of these questions helps to develop confidence, accuracy, and the knack of logical thinking and decision-making skills to ace examinations.
“Probability is one of the highest scoring subjects in Class 12 Mathmatics. you memorize the basic principles of probability, learn all the formulas, and practice the variety of problems related to the probability concepts, the accuracy and speed for the examination are achievable. “The NCERT solution for Mathematics for class 12 chapter “Probability” is divided into step-wise methods so that students can understand any problem without any difficulty” remarks our tutors. You have to practice this chapter rigorously by revising the formula by a regular practice of the NCERT solutions on it to gain accuracy, speed and confidence. A well-prepared “Probability”chapter for a student is surely held in class 12 Board Exams and competitive exams including JEE Main, JEE advanced.
Here are a few key topics outside the NCERT syllabus that students should study for JEE. Learning these will give you an extra edge during the exam.
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We at Careers360 compiled all the NCERT class 12 Maths solutions in one place for easy student reference. The following links will allow you to access them.
Also, read,
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Given below are the class-wise solutions of class 12 NCERT:
Here are some useful links for the NCERT books and the NCERT syllabus for class 12
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Frequently Asked Questions (FAQs)
It is a part of mathematics that's wont to calculate the worth of possibility in which an occasion or an event might occur.
Understanding obscure events becomes easier. Probability class 12 NCERT solution is a topic with high weighting both in boards & competitive tests.
Probability class 12 NCERT solution consists of the following 7 key themes - conditional probability, multiplication theorem and independent events, Law of Total Probability, the theorem of Bayes, random variables and probability distributions.
Each of these steps in these NCERT solutions class 12 probability chapters has been described as thoroughly as possible to make learning about the various probability laws and numerical very easy.
It's crucial. This question topic accounts for a substantial portion of the JEE Main, JEE Advanced, and several other exams.
NCERT Solutions Topics that students require to be accustomed to, in this chapter, primarily include: conditional probability; Bayes' theorem, and random variables.
With regular practice of the NCERT textbook questions and revising important formulas with speed can help you improve accuracy in solving the problems. Practicing with prior years papers may lead the students to gain command over the area.
Most errors while practicing this chapter arise when learners implement the wrong formula, misunderstand a problem's circumstances, and don't determine correct probabilities.
Yes, NCERT solutions include answers to all of the questions given in the NCERT textbook which you can rely upon completely for exam preparation.
On Question asked by student community
Hello Ananya,
Please specify the class for which you need the question papers. I am providing Class 10 and 12 papers.
Here are the links to the CBSE Half-yearly Question Papers (2025-2026).
Hello Ananya,
Please specify the class for which you need the question papers. I am providing Class 10 and 12 papers.
Here are the links to the CBSE Half-yearly Question Papers (2025-2026).
Hello Pawan,
CBSE Class 10 Mathematics 2026 and previous year question paper:
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CBSE Class 12 Mathematics 2026 and previous year question paper:
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Check the link below to download NCERT Class 12 previous year question papers in PDF format for all subjects.
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