🟪 1-Minute Summary
Probability measures the likelihood of an event occurring, ranging from 0 (impossible) to 1 (certain). Key concepts include sample space, events, independent vs dependent events, and conditional probability. Understanding probability is foundational for hypothesis testing, Bayes theorem, and machine learning.
🟦 Core Notes (Must-Know)
Basic Definitions
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Sample Space and Events
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Probability Rules
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Independent vs Dependent Events
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Conditional Probability
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🟨 Interview Triggers (What Interviewers Actually Test)
Common Interview Questions
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“What’s the difference between independent and dependent events?”
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“Explain conditional probability with an example”
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🟥 Common Mistakes (Traps to Avoid)
Mistake 1: Confusing independence with mutual exclusivity
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🟩 Mini Example (Quick Application)
Scenario
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Solution
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🔗 Related Topics
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