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JEE Main & Advanced Focus Reading Time: 12 min 5 Key Concepts

Conditional Probability: The "Given That" World

Master the art of solving "given that" probability problems with Bayes' Theorem and real-world applications for JEE success.

100%
JEE Relevance
5
Key Concepts
8+
Examples
15min
Avg. Solve Time

Why Conditional Probability Matters in JEE

Conditional probability appears in 2-3 questions per JEE paper, making it essential for scoring well. Understanding "given that" scenarios helps you:

  • Solve complex real-world probability problems
  • Apply Bayes' Theorem effectively
  • Avoid common probability pitfalls
  • Gain 4-6 marks with confidence

The Fundamental Formula

$P(A|B) = \frac{P(A \cap B)}{P(B)}$

Probability of A given B equals Probability of A and B divided by Probability of B

Concept 1 Easy

Understanding "Given That"

Conditional probability $P(A|B)$ means we're only considering the cases where B has already happened.

Key Insight:

The sample space shrinks to only those outcomes where B occurs.

Example: Dice Problem

When rolling a fair die, what is the probability of getting a 3 given that the number is odd?

Step 1: Identify events:

• A = Getting a 3

• B = Getting an odd number {1, 3, 5}

Step 2: Apply formula: $P(A|B) = \frac{P(A \cap B)}{P(B)}$

Step 3: Calculate:

• $P(A \cap B) = P(\text{3}) = \frac{1}{6}$

• $P(B) = P(\text{odd}) = \frac{3}{6} = \frac{1}{2}$

Step 4: $P(A|B) = \frac{1/6}{1/2} = \frac{1}{3}$

Concept 2 Medium

Independent vs Dependent Events

Understanding when events affect each other is crucial for correct probability calculations.

Independent Events:

$P(A|B) = P(A)$ - Knowing B occurred doesn't change A's probability

Dependent Events:

$P(A|B) \neq P(A)$ - B's occurrence affects A's probability

Example: Card Problem

From a standard deck, what's the probability of drawing a king given that the card is a face card?

Step 1: Identify events:

• A = Drawing a king

• B = Drawing a face card (Jack, Queen, King)

Step 2: $P(A|B) = \frac{P(A \cap B)}{P(B)} = \frac{P(\text{King})}{P(\text{Face Card})}$

Step 3: Calculate:

• Kings that are face cards: 4 cards

• Total face cards: 12 cards

Step 4: $P(A|B) = \frac{4}{12} = \frac{1}{3}$

Concept 3 Hard

Bayes' Theorem

The powerful theorem for reversing conditional probabilities.

Bayes' Theorem Formula

$P(A|B) = \frac{P(B|A) \cdot P(A)}{P(B)}$

When to Use Bayes' Theorem:

  • Medical testing (disease given positive test)
  • Quality control (defective given failed test)
  • Spam filtering (spam given certain words)

Example: Medical Testing

A disease affects 1% of population. Test is 99% accurate (99% true positive, 99% true negative). If someone tests positive, what's the probability they actually have the disease?

Step 1: Define events:

• D = Has disease, $P(D) = 0.01$

• T+ = Tests positive

Step 2: Known probabilities:

• $P(T+|D) = 0.99$ (true positive rate)

• $P(T+|\text{not } D) = 0.01$ (false positive rate)

Step 3: Apply Bayes':

$P(D|T+) = \frac{P(T+|D)P(D)}{P(T+|D)P(D) + P(T+|\text{not } D)P(\text{not } D)}$

Step 4: Calculate:

$P(D|T+) = \frac{0.99 \times 0.01}{0.99 \times 0.01 + 0.01 \times 0.99} = \frac{0.0099}{0.0099 + 0.0099} = 0.5$

Surprising Result: Only 50% chance of actually having disease despite positive test!

🚀 Conditional Probability Problem-Solving Strategies

For "Given That" Problems:

  • Always identify what's "given" first
  • Shrink your sample space to the given condition
  • Use Venn diagrams for visualization
  • Check if events are independent

For Bayes' Theorem Problems:

  • Clearly define all events
  • Calculate total probability carefully
  • Use tree diagrams for complex cases
  • Always interpret your final answer

Concepts 4-5 Available in Full Version

Includes Total Probability Theorem and Advanced Bayes' Applications with JEE-level problems

📝 Quick Self-Test

Try these JEE-level conditional probability problems:

1. In a family with two children, given that at least one is a boy, what's the probability that both are boys?

2. A bag contains 3 red and 4 blue balls. Two balls are drawn without replacement. What's the probability the second is red given that the first was blue?

3. Three machines produce items. Machine A makes 50% with 2% defective, B makes 30% with 3% defective, C makes 20% with 4% defective. If an item is defective, what's the probability it came from machine A?

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