A comprehensive platform for Teachers to create standard question papers and Students to practice Case-Based, Assertion-Reason, and Critical Thinking questions.
Create professional PDF/Word papers with logo, instructions, and mixed question types in minutes.
Explore our repository by Class and Topic. Filter by "Knowledge" or "Competency" levels.
For Students. Take timed MCQ tests to check your understanding. Get instant feedback.
According to NEP 2020, rote learning is out. The focus has shifted to assessing a student's ability to apply concepts in real-life situations.
Questions derived from real-world passages to test analytical skills.
Testing the logic behind concepts, not just the definition.
Open-ended scenarios that require thinking beyond the textbook.
We provide complete AI-Powered Explanations for every question.
(a) Let A be the event that the student knows the answer, and C be the event that the student answers correctly. We are given:
P(A) = 3/5 (probability that the student knows the answer)
P(A') = 2/5 (probability that the student guesses)
P(C|A) = 1 (probability of answering correctly given the student knows the answer)
P(C|A') = 1/3 (probability of answering correctly given the student guesses)
We want to find P(A|C), the probability that the student knows the answer given that they answered correctly. Using Bayes' Theorem:
P(A|C) = [P(C|A) * P(A)] / [P(C|A) * P(A) + P(C|A') * P(A')]
P(A|C) = [1 * (3/5)] / [1 * (3/5) + (1/3) * (2/5)]
P(A|C) = (3/5) / (3/5 + 2/15)
P(A|C) = (3/5) / (9/15 + 2/15)
P(A|C) = (3/5) / (11/15)
P(A|C) = (3/5) * (15/11)
P(A|C) = 9/11
(b) Let X be the random variable representing the value of the prize. The possible values of X are ₹8, ₹4, and ₹2. The probabilities of drawing each prize are:
P(X = 8) = 2/10 = 1/5
P(X = 4) = 5/10 = 1/2
P(X = 2) = 3/10
The mean value of the prize, E(X), is calculated as:
E(X) = Σ [x * P(x)]
E(X) = (8 * 1/5) + (4 * 1/2) + (2 * 3/10)
E(X) = 8/5 + 4/2 + 6/10
E(X) = 1.6 + 2 + 0.6
E(X) = 4.2
Correct Answer: (a) 9/11 OR (b) ₹4.2