CS109
  • Lectures
    • Week 1
    • 1 - Counting
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    • 2 - Permutations and Combinations
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    • 3 - Axioms of Probability
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    • Week 2
    • 4 - Conditional Probability and Bayes
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    • 5 - Independence
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    • 6 - Random Variables and Expectation
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    • Week 3
    • 7 - Variance, Bernoulli, Binomial
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    • 8 - Poisson and More
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    • 9 - Continuous Random Variables
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    • Week 4
    • 10 - The Normal Distribution
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    • 11 - Joint Distributions
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    • 12 - Independent Random Variables
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    • Week 5
    • 13 - Joint Random Variable Statistics
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    • 14 - Conditional Expectation
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    • 15 - General Inference
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    • Week 6
    • 16 - Continuous Joint Distributions I
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    • 17 - Continuous Joint Distributions II
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    • 18 - Central Limit Theorem
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    • Week 7
    • 19 - Sampling/Bootstrapping
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    • 20 - Parameters and MLE
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    • 21 - Beta
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    • Week 8
    • 22 - Maximum A Posteriori
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    • 23 - Naive Bayes
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    • Week 9
    • 24 - Gradient Ascent and Linear Regression
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    • 25 - Logistic Regression
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    • 26 - Utility of Money, Simulating Probabilities, and Jensen's Inequality
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    • Week 10
    • 27 - Deep Learning & Beyond CS109
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    • Section 7
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Problem Set 2: Core Probability

Due: Monday, April 27, 10:00AM Pacific Time


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Problem Set


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