CBSE Class 12th Exam Date:17 Feb' 26 - 17 Feb' 26
NCERT Solutions for Exercise 13.5 Class 12 Maths Chapter 13 Probability are discussed here. These NCERT solutions are created by subject matter expert at Careers360 considering the latest syllabus and pattern of CBSE 2023-24. In this article, you will get NCERT solutions for exercise 13.5 Class 12 Maths chapter 13 prepared by subject matter experts who know how to write answers in board exams. Some important concepts like Bernoulli Trials and Binomial Distribution in probability are covered in this exercise 13.5 Class 12 Maths solutions. There are 3 examples related to Bernoulli trials and Binomial distribution are given in the NCERT textbook. First, try to solve these examples, you will get to know about Bernoulli trials. There are 15 questions given in the NCERT textbook exercise 13.5. You should try to solve all the NCERT Maths syllabus problems on your own. If you find difficulties while solving these problems, you can take help from Class 12 Maths chapter 13 exercise 13.5 solutions.
12th class Maths exercise 13.5 answers are designed as per the students demand covering comprehensive, step by step solutions of every problem. Practice these questions and answers to command the concepts, boost confidence and in depth understanding of concepts. Students can find all exercise enumerated in NCERT Book together using the link provided below.
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Question:1(i) A die is thrown 6 times. If ‘getting an odd number’ is a success, what is the probability of
5 successes?
Answer:
X be the number of success of getting an odd number.
$P(probability\, of\, getting\, odd\, number)=\frac{3}{6}=\frac{1}{2}$
$\therefore \, \, \, \, q=1-P=1-\frac{1}{2}=\frac{1}{2}$
X has a binomial distribution.
$\therefore P(X=x)=^nC_n - x.q^{n-x}.p^x$![]()
$P(X=x)=^6C_6 -x.$
$(\frac{1}{2})^{6-x} . (\frac{1}{2})^{x}$![]()
$P(X=x)=^6C_6-x.$
$(\frac{1}{2})^{6}$![]()
$P(5\, \, \, success) =P(x=5)$![]()
$= ^6C_5 .(\frac{1}{2})^6$
$= 6 .(\frac{1}{64})$
$= \frac{3}{32}$
Question:1(ii) A die is thrown 6 times. If ‘getting an odd number’ is a success, what is the probability of
at least 5 successes?
Answer:
X be a number of success of getting an odd number.
$P(probability\, of\, getting\, odd\, number)=\frac{3}{6}=\frac{1}{2}$
$\therefore \, \, \, \, q=1-P=1-\frac{1}{2}=\frac{1}{2}$
X has a binomial distribution.
$\therefore\ P(X=x)=^nC_n - x.q^{n-x}.p^x$![]()
$P(X=x)=^6C_6-x.$
$(\frac{1}{2})^{6-x} . (\frac{1}{2})^{x}$![]()
$P(X=x)=^6C_6-x.$
$(\frac{1}{2})^{6}$![]()
$P(At \, \, least \, \, 5\, \, \, success) =P(x\geq 5)$
$=P(X=5)+P(X=6)$
$= ^6C_5 .(\frac{1}{2})^6+^6C_6 .(\frac{1}{2})^6$
$= 6 .(\frac{1}{64})$$+ (\frac{1}{64})$
$= \frac{7}{64}$
Question:1(iii) A die is thrown 6 times. If ‘getting an odd number’ is a success, what is the probability of
at most 5 successes?
Answer:
X be a number of success of getting an odd number.
$P(probability\, of\, getting\, odd\, number)=\frac{3}{6}=\frac{1}{2}$
$\therefore \, \, \, \, q=1-P=1-\frac{1}{2}=\frac{1}{2}$
X has a binomial distribution.
$\therefore\ P(X=x)=^nC_n - x.q^{n-x}.p^x$![]()
$P(X=x)=^6C_6-x.$
$(\frac{1}{2})^{6-x} . (\frac{1}{2})^{x}$![]()
$P(X=x)=^6C_6-x.$
$(\frac{1}{2})^{6}$![]()
$P(atmost\, \, 5\, \, \, success) =P(x\leq 5)$
$=1-P(X> 5)$
$=1-P(X= 5)$
$= 1-^6C_6 .(\frac{1}{2})^6$
$= 1- (\frac{1}{64})$
$= \frac{63}{64}$
Answer:
A pair of dice is thrown $4$ times.X be getting a doublet.
Probability of getting doublet in a throw of pair of dice :
$P=\frac{6}{36}=\frac{1}{6}$
$q=1-P=1-\frac{1}{6}=\frac{5}{6}$
X has a binomial distribution,n=4
$\therefore \, \, \, \, P(X=x)=^nC_x.q^{n-x}.p^x$
$P(X=x)=^4C_x.$$(\frac{5}{6})^{4-x} . (\frac{1}{6})^{x}$
$P(X=x)=^4C_x.$$\frac{5^{4-x}}{6^4}$
Put x = 2
$P(X=2)=^4C_2.$ $\frac{5^{4-2}}{6^4}$
$P(X=2)=6\times \frac{25}{1296}$
$P(X=2)= \frac{25}{216}$
Answer:
There are $5^{o}/_{o}$ defective items in a large bulk of items.
X denotes the number of defective items in a sample of 10.
$\Rightarrow \, \, P=\frac{5}{100}=\frac{1}{2}$
$\Rightarrow \, \, q=1-\frac{1}{20}=\frac{19}{20}$
X has a binomial distribution, n=10.
$\therefore \, \, \, \, P(X=x)=^nC_x.q^{n-x}.p^x$
$P(X=x)=^1^0C_x.$$(\frac{19}{20})^{10-x} . (\frac{1}{20})^{x}$
$P(not\, more\, than\, one\, defective item)=p(X\leq 1)$
$=P(X=0)+P(X=1)$
$=^{10}C_0(\frac{19}{20})^{10} . (\frac{1}{20})^{0}+^{10}C_1(\frac{19}{20})^{9} . (\frac{1}{20})^{1}$
$=(\frac{19}{20})^{9} . (\frac{29}{20})^{1}$
Question:4(i) Five cards are drawn successively with replacement from a well-shuffled deck of $52$ cards. What is the probability that
all the five cards are spades?
Answer:
Let X represent a number of spade cards among five drawn cards. Five cards are drawn successively with replacement from a well-shuffled deck of $52$ cards.
We have 13 spades.
$P=\frac{13}{52}=\frac{1}{4}$
$q=1-P=1-\frac{1}{4}=\frac{3}{4}$
X has a binomial distribution,n=5.
$\therefore \, \, \, \, P(X=x)=^nC_x.q^{n-x}.p^x$
$P(X=x)=^5C_x.$$(\frac{3}{4})^{5-x} . (\frac{1}{4})^{x}$
Put X=5 ,
$P(X=5)=^5C_5.$$(\frac{3}{4})^{0} . (\frac{1}{4})^{5}$
$=1\times \frac{1}{1024}$
$= \frac{1}{1024}$
Question:4(ii) Five cards are drawn successively with replacement from a well-shuffled deck of 52 cards. What is the probability that
only 3 cards are spades?
Answer:
Let X represent a number of spade cards among five drawn cards. Five cards are drawn successively with replacement from a well-shuffled deck of $52$ cards.
We have 13 spades.
$P=\frac{13}{52}=\frac{1}{4}$
$q=1-P=1-\frac{1}{4}=\frac{3}{4}$
X has a binomial distribution,n=5.
$\therefore \, \, \, \, P(X=x)=^nC_x.q^{n-x}.p^x$
$P(X=x)=^5C_x.$$(\frac{3}{4})^{5-x} . (\frac{1}{4})^{x}$
Put X=3 ,
$P(X=3)=^5C_3.$$(\frac{3}{4})^{2} . (\frac{1}{4})^{3}$
$=10\times \frac{9}{16}\times \frac{1}{64}$
$=\frac{45}{512}$
Question:4(iii) Five cards are drawn successively with replacement from a well-shuffled deck of 52 cards. What is the probability that
none is a spade?
Answer:
Let X represent number of spade cards among five drawn cards. Five cards are drawn successively with replacement from a well-shuffled deck of $52$ cards.
We have 13 spades .
$P=\frac{13}{52}=\frac{1}{4}$
$q=1-P=1-\frac{1}{4}=\frac{3}{4}$
X has a binomial distribution,n=5.
$\therefore \, \, \, \, P(X=x)=^nC_x.q^{n-x}.p^x$
$P(X=x)=^5C_x.$$(\frac{3}{4})^{5-x} . (\frac{1}{4})^{x}$
Put X=0 ,
$P(X=0)=^5C_0.$$(\frac{3}{4})^{5} . (\frac{1}{4})^{0}$
$=1\times \frac{243}{1024}$
$= \frac{243}{1024}$
none will fuse after $150$ days of use.
Answer:
Let X represent number of bulb that will fuse after $150$ days of use .Trials =5
$P=0.005$
$q=1-0.005=1-0.005=0.95$
X has a binomial distribution,n=5.
$\therefore \, \, \, \, P(X=x)=^nC_x.q^{n-x}.p^x$
$P(X=x)=^5C_x.$$(0.95)^{5-x} . (0.05)^{x}$
Put X=0 ,
$P(X=0)=^5C_0.$$(0.95)^{5} . (0.05)^{0}$
$=(0.95)^{5}$
not more than one will fuse after $150$ days of use.
Answer:
Let X represent a number of the bulb that will fuse after $150$ days of use. Trials =5
$P=0.005$
$q=1-0.005=1-0.005=0.95$
X has a binomial distribution,n=5.
$\therefore \, \, \, \, P(X=x)=^nC_x.q^{n-x}.p^x$
$P(X=x)=^5C_x.$$(0.95)^{5-x} . (0.05)^{x}$
Put $X\leq 1$ ,
$P(X\leq 1)=P(X=0)+P(X=1)$
$=^5C_0.$$(0.95)^{5} . (0.05)^{0}+^5C_1 (0.95)^{4} . (0.05)^{1}$
$=(0.95)^{5}+ (0.25)(0.95)^4$
$=(0.95)^{4}(0.95+ 0.25)$
$=(0.95)^{4}\times 1.2$
Question:5(iii) 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
more than one will fuse after$150$ days of use.
Answer:
Let X represent number of bulb that will fuse after $150$ days of use .Trials =5
$P=0.005$
$q=1-0.005=1-0.005=0.95$
X has a binomial distribution,n=5.
$\therefore \, \, \, \, P(X=x)=^nC_x.q^{n-x}.p^x$
$P(X=x)=^5C_x.$$(0.95)^{5-x} . (0.05)^{x}$
Put $X> 1$ ,
$P(X> 1)=1-(P(X=0)+P(X=1))$
$=1-(^5C_0.$$(0.95)^{5} . (0.05)^{0}+^5C_1 (0.95)^{4} . (0.05)^{1})$
$=1-((0.95)^{5}+ (0.25)(0.95)^4)$
$=1-((0.95)^{4}(0.95+ 0.25))$
$=1-(0.95)^{4}\times 1.2$
at least one will fuse after $150$ days of use.
Answer:
Let X represent number of bulb that will fuse after $150$ days of use .Trials =5
$P=0.005$
$q=1-0.005=1-0.005=0.95$
X has a binomial distribution,n=5.
$\therefore \, \, \, \, P(X=x)=^nC_x.q^{n-x}.p^x$
$P(X=x)=^5C_x.$$(0.95)^{5-x} . (0.05)^{x}$
Put $X\geq 1$ ,
$P(X\geq 1)=1-P(X< 1)$
$P(X\geq 1)=1-P(X=0)$
$=1-^5C_0.$$(0.95)^{5} . (0.05)^{0}$
$=1-(0.95)^{5}$
Answer:
Let X denote a number of balls marked with digit 0 among 4 balls drawn.
Balls are drawn with replacement.
X has a binomial distribution,n=4.
$P=\frac{1}{10}$
$q=1-P=1-\frac{1}{10}=\frac{9}{10}$
$\therefore \, \, \, \, P(X=x)=^nC_x.q^{n-x}.p^x$
$P(X=x)=^4C_x.$$(\frac{9}{10})^{4-x} . (\frac{1}{10})^{x}$
Put X = 0,
$P(X=0)=^4C_0.$$(\frac{9}{10})^{4} . (\frac{1}{10})^{0}$
$= 1.(\frac{9}{10})^{4}$
$= (\frac{9}{10})^4$
Answer:
Let X represent the number of correctly answered questions out of 20 questions.
The coin falls heads, he answers 'true'; if it falls tails, he answers 'false'.
$P=\frac{1}{2}$
$q=1-P=1-\frac{1}{2}=\frac{1}{2}$
X has a binomial distribution,n=20
$\therefore \, \, \, \, P(X=x)=^nC_x.q^{n-x}.p^x$
$P(X=x)=^2^0C_x.$$(\frac{1}{2})^{20-x} . (\frac{1}{2})^{x}$
$P(X=x)=^2^0C_x.$ $(\frac{1}{2})^{20}$
$P(at\, \, least\, 12\, \,questions \, \, answered\, \, correctly)=P(X\geq 12)$
$=P(X=12)+P(X=13)..................+P(X=20)$
$=^{20}C_1_2 (\frac{1}{2})^{20}+^{20}C_1_3(\frac{1}{2})^{20}+..........^{20}C_2_0 (\frac{1}{2})^{20}$
$=(\frac{1}{2})^{20}(^{20}C_1_2 +^{20}C_1_3+..........^{20}C_2_0 )$
(Hint : $P(X=3)$ is the maximum among all of $P(x_{i})$ ,$x_{i}=0,1,2,3,4,5,6$ )
Answer:
X is a random variable whose binomial distribution is $B\left [ 6,\frac{1}{2} \right ].$
Here , n=6 and $P=\frac{1}{2}$.
$\therefore \, \,q=1-P= 1-\frac{1}{2}= \frac{1}{2}$
$\therefore \, \, \, \, P(X=x)=^nC_x.q^{n-x}.p^x$
$=^{6}C_x .(\frac{1}{2})^{6-x}(\frac{1}{2})^x$
$=^{6}C_x (\frac{1}{2})^6$
$P(X=x)$ is maximum if $^{6}C_x$ is maximum.
$^{6}C_0 =^{6}C_6 =\frac{6!}{0!.6!}=1$
$^{6}C_1 =^{6}C_5 =\frac{6!}{1!.5!}=6$
$^{6}C_2 =^{6}C_4 =\frac{6!}{2!.4!}=15$
$^{6}C_3 =\frac{6!}{3!.3!}=20$
$^{6}C_3$ is maximum so for x=3 ,$P(X=3)$ is maximum.
Answer:
Let X represent number of correct answers by guessing in set of 5 multiple choice questions.
Probability of getting a correct answer :
$P=\frac{1}{3}$
$\therefore q=1-P=1-\frac{1}{3}=\frac{2}{3}$
X has a binomial distribution,n=5.
$\therefore \, \, \, \, P(X=x)=^nC_x.q^{n-x}.p^x$
$P(X=x)=^5C_x.$$(\frac{2}{3})^{5-x} . (\frac{1}{3})^{x}$
$P(guessing \, \, more\, \, than \, 4\, correct\, answer)=P(X\geq 1)$
$=P(X=4)+P(X=5)$
$=^5C_4.$$(\frac{2}{3})^{1} . (\frac{1}{3})^{4}+^5C_5(\frac{2}{3})^{0} . (\frac{1}{3})^{5}$
$=\frac{10}{243}+\frac{1}{243}$
$=\frac{11}{243}$
at least once
Answer:
Let X represent number of winning prizes in 50 lotteries .
$P=\frac{1}{100}$
$q=1-P=1-\frac{1}{100}=\frac{99}{100}$
X has a binomial distribution,n=50.
$\therefore \, \, \, \, P(X=x)=^nC_x.q^{n-x}.p^x$
$P(X=x)=^50C_x.$$(\frac{1}{100})^{50-x} . (\frac{99}{100})^{x}$
$P(winning \:at\: least\: once)=P(X\geq 1)$
$=1-P(X< 1)$
$=1-P(X= 0)$
$=1- ^{50}C_0 (\frac{99}{100})^{50}$
$=1- 1. (\frac{99}{100})^{50}$
$=1- (\frac{99}{100})^{50}$
exactly once
Answer:
Let X represent number of winning prizes in 50 lotteries .
$P=\frac{1}{100}$
$q=1-P=1-\frac{1}{100}=\frac{99}{100}$
X has a binomial distribution,n=50.
$\therefore \, \, \, \, P(X=x)=^nC_x.q^{n-x}.p^x$
$P(X=x)=^50C_x.$$(\frac{1}{100})^{50-x} . (\frac{99}{100})^{x}$
$P(winning\, exactly\, once)=P(X= 1)$
$=^{50}C_1 (\frac{99}{100})^{49}.\frac{1}{100}$
$= 50.(\frac{99}{100})^{49}\frac{1}{100}$
$=\frac{1}{2} (\frac{99}{100})^{50}$
at least twice?
Answer:
Let X represent number of winning prizes in 50 lotteries.
$P=\frac{1}{100}$
$q=1-P=1-\frac{1}{100}=\frac{99}{100}$
X has a binomial distribution,n=50.
$\therefore \, \, \, \, P(X=x)=^nC_x.q^{n-x}.p^x$
$P(X=x)=^50C_x.$$(\frac{1}{100})^{50-x} . (\frac{99}{100})^{x}$
$P(winning \, \, at \, \, least \, \, twice)=P(X\geq 2)$
$=1-P(X< 2)$
$=1-P(X\leq 1)$
$=1-(P(X=0)+P(X=1))$
$=1- (\frac{99}{100})^{50}-\frac{1}{2}(\frac{99}{100})^{49}$
$=1- (\frac{99}{100})^{49}(\frac{1}{2}+\frac{99}{100})$
$=1- (\frac{99}{100})^{49}\frac{149}{100}$
Question:11 Find the probability of getting $5$ exactly twice in $7$ throws of a die.
Answer:
Let X represent number of times getting 5 in 7 throws of a die.
Probability of getting 5 in single throw of die=P
$P=\frac{1}{6}$
$q=1-P=1-\frac{1}{6}=\frac{5}{6}$
X has a binomial distribution,n=7
$\therefore \, \, \, \, P(X=x)=^nC_x.q^{n-x}.p^x$
$P(X=x)=^7C_x.$$(\frac{5}{6})^{7-x} . (\frac{1}{6})^{x}$
$P(getting\, \, exactly\, \, twice)=P(X= 2)$
$=^{7}C_2 (\frac{5}{6})^{5}\frac{1}{6}^2$
$=21 (\frac{5}{6})^{5}\frac{1}{36}$
$= (\frac{5}{6})^{5}\frac{7}{12}$
Question:12 Find the probability of throwing at most $2$ sixes in $6$ throws of a single die.
Answer:
Let X represent number of times getting 2 six in 6 throws of a die.
Probability of getting 6 in single throw of die=P
$P=\frac{1}{6}$
$q=1-P=1-\frac{1}{6}=\frac{5}{6}$
X has a binomial distribution,n=6
$\therefore \, \, \, \, P(X=x)=^nC_x.q^{n-x}.p^x$
$P(X=x)=^6C_x.$$(\frac{5}{6})^{6-x} . (\frac{1}{6})^{x}$
$P(getting\, \, atmost\, \, two\, six)=P(X\leq 2)$
$=P(X=0)+P(X=1)+P(X=2)$
$=^{6}C_0 (\frac{5}{6})^{6}\frac{1}{6}^0+^{6}C_1 (\frac{5}{6})^{5}\frac{1}{6}^1+^{6}C_2 (\frac{5}{6})^{4}\frac{1}{6}^2$
$=1.(\frac{5}{6})^{6}+6. (\frac{5}{6})^{5}\frac{1}{6}+15 (\frac{5}{6})^{4}\frac{1}{36}$
$=(\frac{5}{6})^{6}+ (\frac{5}{6})^{5}+ (\frac{5}{6})^{4}\frac{5}{12}$
$=(\frac{5}{6})^{4}( \frac{5}{6}^{2}+ \frac{5}{6}+\frac{5}{12})$
$=(\frac{5}{6})^{4}( \frac{25}{36}+ \frac{5}{6}+\frac{5}{12})$
$=(\frac{5}{6})^{4}( \frac{70}{36})$
$=(\frac{5}{6})^{4}( \frac{35}{18})$
Answer:
Let X represent a number of times selecting defective items out of 12 articles.
Probability of getting a defective item =P
$P=10\%=\frac{10}{100}=\frac{1}{10}$
$q=1-P=1-\frac{1}{10}=\frac{9}{10}$
X has a binomial distribution,n=12
$\therefore \, \, \, \, P(X=x)=^nC_x.q^{n-x}.p^x$
$P(X=x)=^1^2C_x.$$(\frac{9}{10})^{12-x} . (\frac{1}{10})^{x}$
$P(selectting\, \, 9\,defective \, items)=$
$=^{12}C_9 (\frac{9}{10})^{3}\frac{1}{10}^9$
$=220 (\frac{9^3}{10^3})\frac{1}{10^9}$
$=22 \times \frac{9^3}{10^1^1}$
(A) $10^{-1}$
(B) $\left ( \frac{1}{5} \right )^{5}$
(C) $\left ( \frac{9}{10} \right )^{5}$
(D) $\frac{9}{10}$
Answer:
Let X represent a number of defective bulbs out of 5 bulbs.
Probability of getting a defective bulb =P
$P=\frac{10}{100}=\frac{1}{10}$
$q=1-P=1-\frac{1}{10}=\frac{9}{10}$
X has a binomial distribution,n=5
$\therefore \, \, \, \, P(X=x)=^nC_x.q^{n-x}.p^x$
$P(X=x)=^5C_x.$$(\frac{9}{10})^{5-x} . (\frac{1}{10})^{x}$
$P(non\,of \,bulb\,is\, defective \,)=P(X=0)$
$=^{5}C_0 (\frac{9}{10})^{5}\frac{1}{10}^0$
$=1.\frac{9}{10}^5$
$=(\frac{9}{10})^5$
The correct answer is C.
In the following, choose the correct answer:
(A) $^{5}C_{4}\left ( \frac{4}{5} \right )^{4}\frac{1}{5}$
(B) $\left ( \frac{4}{5} \right )^{4}\frac{1}{5}$
(C) $^{5}C_{1}\frac{1}{5}\left ( \frac{4}{5} \right )^{4}$
(D) None of these
Answer:
Let X represent number students out of 5 who are swimmers.
Probability of student who are not swimmers =q
$q=\frac{1}{5}$
$P=1-q=1-\frac{1}{5}=\frac{4}{5}$
X has a binomial distribution,n=5
$\therefore \, \, \, \, P(X=x)=^nC_x.q^{n-x}.p^x$
$P(X=x)=^5C_x.$$(\frac{1}{5})^{5-x} . (\frac{4}{5})^{x}$
$P(4\, \,students\, \, are\, swimmers)=P(X= 4)$
$=^5C_4(\frac{1}{5})^{1} . (\frac{4}{5})^{4}$
Option A is correct.
Bernoulli trials is a very important concept for the finding probability of independents trials where outcomes are only success or failure. In exercise 13.4 Class 12 Maths you will get questions related to Bernoulli Trials and Binomial Distribution. There are 3 examples and 15 questions in this exercise. You must be thorough with Class 12 Maths ch 13 ex 13.5 in order to perform well in board exams. Basic knowledge of permutations and combinations is also required for this exercise.
Also Read| Probability Class 12th Notes
Happy learning!!!
Frequently Asked Questions (FAQs)
Probability theory is a branch of mathematics that deals with the numerical measurement of the degree of uncertainty.
Probability theory is useful in Meteorologists, weather prediction, health, sports, gambling, etc.
The probability of a certain event is 1.
The probability of getting head is 0.5 when a fair coin is tossed.
The probability of getting two consecutive heads when a fair coin is tossed two times is 0.25.
Probability of getting Head = 1 - Probability of getting tail
= 1 - 0.6
= 0.4
Yes, click here to get NCERT Solutions for Class 10 Maths.
Click on the link to get NCERT Solutions for Class 10 Maths Probability.
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