Course: Probability Theory (KSMIC04)

Timings: Mondays and Saturdays 9:00 am to 11:00 am.

Teaching Assistant: Arunkumar

Course meeting venue: Google meet link

Syllabus: Probability space, events. Axioms of probability. Inclusion exclusion principle. Combinatorial examples. Independence and conditioning. Bayes formula. Random variables. Distribution functions. Examples: Binomial, Geometric, Poisson, Hypergeometric etc. Expectation, variance and covariance, generating functions and characteristic function. Independence and conditioning of random variables. Joint disribution, Distribution of the sum.
Continous distributions and densities. Examples: Normal, exponential and gamma, uniform and beta, etc. Inequalities: Markov, Chebyshev, Cauchy-Schwarz, Bonferroni. IID random variables. Weak law of large numbers, CLT. Simple symmetric random walk, reflection priciple, recuurence and transience.

Grading: Biweekly quiz (20%), Mid-term test (30%), End-term test (50%)

References and Resources:

Classroom Scribes

Lecture Date Contents
1 1 November 2021 Introduction, Examples, Probability Spaces
2 6 November 2021 Axioms of probability and illustrations
3 8 November 2021 Inclusion-exclusion principle and examples
4 13 November 2021 Bonferroni inequalities
5 15 November 2021 Independence and conditional probability
6 20 November 2021 Bayes’ rule and applications
7 22 November 2021 Paradoxes, resolutions and other issues
8 27 November 2021 Discrete probability distributions and examples
9 29 November 2021 Continuos probability distributions and examples
10 4 December 2021 Joint distributions and change of variable formula
11 6 December 2021 Expectation, moments and generating functions
12 11 December 2021 Inequalities (Cauchy-Shwarz, Markov, Chebyshev, Chernoff )
  13 December 2021 Mid-Semester
  18 December 2021 Mid-Semester
13 20 December 2021 Conditional distributions and conditional expectation
14 23 December 2021 Make up lecture
15 27 December 2021 Characteristic function and properties
16 1 January 2022 Law of large numbers
17 3 January 2022 Gaussian random variables and properties
18 8 January 2022 Poisson limits
19 10 January 2022 Central limit theorem
20 15 January 2022 Central limit theorem (contd.)
21 17 January 2022 Simulation
22 22 January 2022 Simple symmetric random walk
23 24 January 2022 Recurrence and transience
24 29 January 2022 Reflection Principle
  12 February 2022 End Semester
Problem Sets: Set-1 Set-2 Set-3 Set-4 Set-5 Set-6 Set-7 Set-8