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NCERT Solutions for Class 12 Maths Chapter 13 β Probability Exercise 13.2
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Chapter 13 β Probability Exercise 13.2
1.

Flashcard for Question 1
Quick Tip: Use independence: P(A β© B) = P(A) Γ P(B).
Common Mistake: Adding probabilities or using the union formula instead of multiplying; forgetting this works only if A and B are independent.

2.

Flashcard for Question 2
Quick Tip: Without replacement β multiply sequential probabilities: (26/52) Γ (25/51) = 25/102.
Common Mistake: Treating draws as with replacement (using 26/52 twice), or forgetting to reduce the denominator on the second draw

3.

Flashcard for Question 3
Quick Tip: For βall goodβ without replacement, multiply sequential probabilities: (12/15) Γ (11/14) Γ (10/13).
Common Mistake: Treating draws as with replacement (using 12/15 three times) or accidentally including outcomes with a bad orange.

4.

Flashcard for Question 4
Quick Tip: Check independence using P(A β© B) = P(A) Γ P(B). Calculate each probability separately and compare.
Common Mistake: Assuming independence without verification or mixing up with mutually exclusive events (theyβre different concepts).

5.

Flashcard for Question 5
Quick Tip: Compute P(A), P(B), and P(A β© B). Then check if P(A β© B) = P(A) Γ P(B).
Common Mistake: Confusing colour grouping with even/odd grouping, or forgetting to divide by 6 (total outcomes).
Exam Insight: Always write probabilities as fractions over total outcomes before comparingβthis shows independence clearly and avoids silly mistakes.

6.

Flashcard for Question 6
Quick Tip: For independence, check if P(E β© F) = P(E) Γ P(F).
Common Mistake: Just comparing P(E) + P(F) with 1 or assuming independence without checking the product rule.
Exam Insight: Write down P(E), P(F), and their product firstβif it matches the given P(E β© F), then independent; otherwise, not. This direct method saves time in exams.

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9.

Flashcard for Question 9
Quick Tip: Use De Morganβs law: P(not A and not B) = 1 β P(A βͺ B). Then apply P(A βͺ B) = P(A) + P(B) β P(A β© B).
Common Mistake: Forgetting to subtract P(A β© B) when finding P(A βͺ B), leading to double counting.
Exam Insight: Always reduce the problem to union/intersection formulas first – itβs faster and avoids mistakes in βnot A and not Bβ type questions.

10.

Flashcard for Question 10
Quick Tip: Convert βnot A or not Bβ into 1 β P(A β© B). Then compare P(A β© B) with P(A) Γ P(B) to test independence.
Common Mistake: Mixing up βnot A or not Bβ with βnot (A β© B)β – careless handling of complements often leads to wrong probability.

11.


12.

Flashcard for Question 12
Quick Tip: Use complement: P(at least once odd) = 1 β P(no odd in 3 tosses).
Common Mistake: Trying to count all favourable cases directly instead of using complement, which is much simpler.
Exam Insight: In βat least onceβ problems, always think of the complementβit saves time and avoids messy casework.

13.

Flashcard for Question 13
Quick Tip: Since itβs with replacement, probabilities stay the same for both draws. Use multiplication for sequential events.
Common Mistake: Forgetting replacement ruleβmany students reduce the denominator on the second draw, which is only correct for without replacement.



14.

Flashcard for Question 14
Quick Tip: Use complement for part (i): P(solved) = 1 β P(both fail). For part (ii), add probabilities of βA solves, B failsβ and βB solves, A fails.β
Common Mistake: Forgetting independence when multiplying probabilities of success/failure, or double counting the case when both solve.



15.




16.

Flashcard for Question 16
Quick Tip: Use Venn diagram logic. Apply inclusionβexclusion: P(H βͺ E) = P(H) + P(E) β P(H β© E). Then use conditional probability for (b) and (c).
Common Mistake: Forgetting to subtract the intersection when finding union, or mixing up conditional probability formula P(A|B) = P(A β© B)/P(B).
Exam Insight: Always calculate the βneitherβ case first (complement of union). For conditional parts, directly plug into the formula – this is a common exam scoring area where clarity matters.



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Download Exercise 13.2 NCERT Solutions PDF
You can download the PDF from the link below for offline study
Class 12 Maths Chapter 13 β Probability: All Exercises
| Exercise | Link |
|---|---|
| Exercise 13.1 | View Solutions |
| Exercise 13.3 | View Solutions |
| Miscellaneous Exercise | View Solutions |
Class 12 Probability- Exercise 13.2 Overview
By exposing you to Bayes’ Theoremβa strong idea applied in both theory and real-life problem-solvingβProbability Class 12 NCERT Solutions Exercise 13.2 pushes your grasp of probability to the next level. This exercise teaches students exactly the opposite of how we often view probabilityβhow to calculate the likelihood of an underlying cause when the outcome is known.
For situations involving reversing the conditionsβsuch as determining the cause when the consequence is knownβthis exercise helps students develop a strong conceptual basis. Probability Class 12 NCERT Solutions Exercise 13.2 helps students in properly utilizing Bayes’ Theorem whether it is deciding whether machine generated a defective product or determining the probability of a student belonging to a given group based on their behavior.
Although at first glance this section of the text seems abstract, in data science, artificial intelligence, medical testing, and even meteorology it is absolutely vital. This part’s questions challenge pupils to go backwards, therefore improving their analytical and logical skills.
Mastery of this activity becomes even more crucial with the revised 2025 NCERT syllabus stressing practical applications. Our detailed answers on Cogniks guarantee students not only find the right response but also grasp the application of Bayes’ Theorem in every situation.
FAQs β Probability Class 12 Exercise 13.2 NCERT
The Theorem of Bayes helps you ascertain, from a result, the probability of a cause. This helps one to reverse a conditional probability problem.
Exercise 13.1 is on forward conditional probability. Exercise 13.2 tackles the reversal of probability seen in Bayes’ Theorem.Β
Should events πΈ 1, πΈ 2… E n split the sample space and A is an event, then
β
π΄ β£πΊπ β£π΄ πΊπ β£π΄ πΊπ β£π΄ πΊπ β£π΄ πΊπ β£π΄ πΊπ β£π΄ πΊπ β£π΄ πΊπ β£π΄ πΊπ β£π΄ πΊπ β£π΄ πΊπ β£π΄ πΊπ β£
1 ππ (πΈπ) β
(π β£π΄ β£π).
P(E)= β j=1 n P(Aβ£E j ΟΒ
While memorizing helps you quickly answer questions on tests, comprehending directs you in knowing when to use it.
Of course. False positives and negatives in medical testing; spam filters; artificial intelligence predictions; more all depend on it.Β
Focus on spotting.
β’ The former opportunities
β’ Said is the anticipated outcome.
β’ The conditional likelihood
β’ Methodically use Bayes’ Theorem after that.