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data science-probability

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  • 1.1 Independent Events & Conditional Probability
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Module 1: Probability Axioms & Combinatorics•Lesson 1

1.1 Independent Events & Conditional Probability

### Bayes Rule Foundation
For events $A$ and $B$ where $P(B) > 0$:
$$P(A|B) = \frac{P(A \cap B)}{P(B)}$$
When $A$ and $B$ are independent, $P(A \cap B) = P(A)P(B)$.
Python 3.11
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Interactive Challenge
+60 XP
Challenge Objective

Compute conditional probability P(A|B) and print 'P(A|B): 0.3'.

solution.py
UTF-84 SpacesAuto-saved
cpython3.11:~/workspace
CPython 3.11.8 (WASM)
$python3 -u solution.py
Click "Compile & Run" (or press Ctrl + Enter) to compile AST, verify bytecode, and execute the solution.