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Probabilistic Systems Analysis and Applied Probability >> Content Detail



Calendar / Schedule



Calendar

The calendar below provides information on the course's lecture (L), recitation (R), tutorial (T), and quiz (Q) sessions.


Ses #TopicsKey dates
L1Probability Models and AxiomsProblem set 1 out
T1Tutorial 1
L2Conditioning and Bayes' Rule
R1Recitation 1
L3IndependenceProblem set 2 out

Problem set 1 due
R2Recitation 2
T2Tutorial 2
L4Counting
R3Recitation 3
L5Discrete Random Variables; Probability Mass Functions; ExpectationsProblem set 3 out

Problem set 2 due
R4Recitation 4
T3Tutorial 3
L6Conditional Expectation; Examples
L7Multiple Discrete Random VariablesProblem set 4 out

Problem set 3 due
R5Recitation 5
T4Tutorial 4
L8Continuous Random Variables - I
R6Recitation 6
L9Continuous Random Variables - IIProblem set 5 out

Problem set 4 due
R7Recitation 7
T5Tutorial 5
Q1Quiz 1 (Covers up to L7)
R8Recitation 8
L10Continuous Random Variables and Derived Distributions
R9Recitation 9
T6Tutorial 6
L11More on Continuous Random Variables, Derived Distributions, Convolution
R10Recitation 10
L12TransformsProblem set 6 out

Problem set 5 due
R11Recitation 11
T7Tutorial 7
L13Iterated Expectations, Sum of a Random Number of Random VariablesProblem set 7 out

Problem set 6 due
R12Recitation 12
L14Prediction; Covariance and Correlation
R13Recitation 13
T8Tutorial 8
L15Bernoulli Process
R14Recitation 14
L16Poisson ProcessProblem set 8 out

Problem set 7 due
R15Recitation 15
T9Tutorial 9
Q2Quiz 2 (Covers up to L14)
R16Recitation 16
L17Poisson Process Examples
R17Recitation 17
T10Tutorial 10
L18Markov Chains - IProblem set 9 out

Problem set 8 due
R18Recitation 18
T11Tutorial 11
L19Markov Chains - II
R19Recitation 19
L20Markov Chains - IIIProblem set 10 out

Problem set 9 due
R20Recitation 20
T12Tutorial 12
L21Weak Law of Large Numbers
R21Recitation 21
L22Central Limit TheoremProblem set 10 due
R22Recitation 22
L23Strong Law of Large Numbers
R23Recitation 23
L24Interactive Exploration
R24Recitation 24
Final Exam (During Finals Week)

 








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