CS109
  • Lectures
    • Week 1
    • 1 - Counting
      • Slides
      • Lecture Notes
    • 2 - Permutations and Combinations
      • Slides
      • Lecture Notes
    • 3 - Axioms of Probability
      • Slides
      • Lecture Notes
    • Week 2
    • 4 - Conditional Probability and Bayes
      • Slides
      • Lecture Notes
    • 5 - Independence
      • Slides
      • Lecture Notes
    • 6 - Random Variables and Expectation
      • Slides
      • Lecture Notes
    • Week 3
    • 7 - Variance, Bernoulli, Binomial
      • Slides
      • Lecture Notes
    • 8 - Poisson and More
      • Slides
      • Lecture Notes
    • Week 4
    • 9 - Continuous Random Variables
      • Slides
      • Lecture Notes
    • 10 - The Normal Distribution
      • Slides
      • Lecture Notes
    • 11 - Joint Distributions
      • Slides
      • Lecture Notes
    • Week 5
    • 12 - Continuous Joint Distributions
      • Slides
      • Lecture Notes
    • 13 - Independent Random Variables
      • Slides
      • Lecture Notes
    • 14 - Conditional Distributions
      • Slides
      • Lecture Notes
    • Week 6
    • 15 - Correlation and Covariance
      • Slides
      • Lecture Notes
    • 16 - Great Expectations
      • Slides
      • Lecture Notes
    • 17 - Beta
      • Slides
      • Lecture Notes
    • Week 7
    • 18 - Central Limit Theorem
      • Slides
      • Lecture Notes
    • 19 - Sampling/Bootstrapping
      • Slides
      • Lecture Notes
    • Week 8
    • 20 - General Inference
      • Slides
      • Lecture Notes
    • 21 - Parameters and MLE
      • Slides
      • Lecture Notes
    • 22 - Gradient Ascent
      • Slides
      • Lecture Notes
    • Week 9
    • 23 - Maximum A Posteriori
      • Slides
      • Lecture Notes
    • 24 - Naive Bayes
      • Slides
      • Lecture Notes
    • 25 - Logistic Regression
      • Slides
      • Lecture Notes
    • Week 10
    • 26 - Deep Learning
      • Slides (Coming Soon)
      • Lecture Notes
    • 27 - CS109 Review
      • Slides
  • Problem Sets
    • Problem Set 1
    • Problem Set 2
    • Problem Set 3
    • Problem Set 4
    • Problem Set 5
    • Problem Set 6
    • PS 1 Solution
    • PS 2 Solution
    • PS 3 Solution
    • PS 4 Solution
    • PS 5 Solution
    • PS 6 Solution
    • Midterm
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  • Section
    • Section 1
    • Handout
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    • Concept Check
    • Section 2
    • Handout
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    • Notebook
    • Notebook Solution
    • Concept Check
    • Section 3
    • Handout
    • Solutions
    • Concept Check
    • Section 4
    • Handout
    • Solutions
    • Notebook
    • Notebook Solution
    • Concept Check
    • Section 5
    • Handout
    • Solutions
    • Concept Check
    • Section 6
    • Handout
    • Solutions
    • Concept Check
    • Section 7
    • Handout
    • Solutions
    • Notebook
    • Notebook Solution
    • Concept Check
    • Section 8
    • Handout
    • Solutions
    • Notebook
    • Notebook Solution
    • Concept Check
    • Section 9
    • Handout
    • Solutions
    • Section Attendance
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    • Administrivia
    • Calculation Ref
    • Python for Probability
    • Python Session Slides
    • Standard Normal Table
    • Normal CDF Calculator
    • Midterm Info/Practice
    • Final Info/Practice
    • Serendipity
    • Medical Bayes
    • Galton Board (Binomial)
    • Jurors
    • Federalist Papers
    • Dart (Joint)
    • Beta
    • Bootstrap
    • WebMD (Inference)
    • MLE and Gradient Ascent
  • Staff / Office Hours
  • Schedule

Problem Set 3: Random Variables

Due: Wednesday, February 5, 1:00PM Pacific Time


Resources



Problem Set 3


Starter Code


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