This is an archived course. A more recent version may be available at ocw.mit.edu.

Advanced Search
    Archived Versions

    Readings

    Text

    This section contains the reading assignments from the course textbook: Bertsekas, Dimitri P., and John N. Tsitsiklis. Introduction to Probability. Belmont, MA: Athena Scientific Press , June 2002. ISBN: 188652940X.

    Recommended Texts

    Drake, A. Fundamentals of Applied Probability Theory. New York, NY: McGraw-Hill, 1988. ISBN: 0070178151.

    Ross, S. A First Course in Probability. Upper Saddle River, NJ: Prentice Hall, 2005. ISBN: 0131856626.

    Ses # Topics readings
    L1 Probability Models and Axioms Sections 1.1-1.2
    L2 Conditioning and Bayes' Rule Sections 1.3-1.4
    L3 Independence Section 1.5
    L4 Counting Section 1.6
    L5 Discrete Random Variables; Probability Mass Functions; Expectations Sections 2.1-2.4
    L6 Conditional Expectation; Examples Sections 2.4-2.6
    L7 Multiple Discrete Random Variables Section 2.7
    L8 Continuous Random Variables - I Sections 3.1-3.3
    L9 Continuous Random Variables - II Sections 3.4-3.5
    Q1 Quiz 1 (Covers up to L7)  
    L10 Continuous Random Variables and Derived Distributions Section 3.6
    L11 More on Continuous Random Variables, Derived Distributions, Convolution Section 4.2
    L12 Transforms Section 4.1
    L13 Iterated Expectations, Sum of a Random Number of Random Variables Sections 4.3-4.4
    L14 Prediction; Covariance and Correlation Sections 4.5-4.6
    L15 Bernoulli Process Section 5.1
    L16 Poisson Process Section 5.2
    Q2 Quiz 2 (Covers up to L14)  
    L17 Poisson Process Examples Section 5.2
    L18 Markov Chains - I Sections 6.1-6.2
    L19 Markov Chains - II Section 6.3
    L20 Markov Chains - III Section 6.4
    L21 Weak Law of Large Numbers Sections 7.1-7.3
    L22 Central Limit Theorem Section 7.4
    L23 Strong Law of Large Numbers Section 7.5
    L24 Interactive Exploration  
      Final Exam (During Finals Week)