SI417: Introduction to Probability Theory (2018-19)
Course Instructor: S. Baskar
Course Name: Introduction to Probability Theory
Credits: 8
Course Type: Minor
Prerequisites: None
Assignments: Strong emphasis on proofs and theory. Numerical problems were easy. Problems required rigorous proofs and justification
Advanced Follow-up Courses: SI402 Statistical Inference, SI404 Applied Stochastic Processes, SI527 Introduction to derivative pricing
Pro Tips: Heavy focus on abstract theory of probability. Write proper proofs.
Course Name: Introduction to Probability Theory
Credits: 8
Course Type: Minor
Prerequisites: None
Course Content: Axioms of probability theory, Countable and uncountable sample spaces and their sigma fields, properties of probability measure, de Morgan's laws, inclusion-exclusion principle, conditional probability, Bayes' theorem, Random variables and random vectors and their distribution and density functions, expectations and moments, moment generating functions, convergence of sequence of random variables, proofs of limit theorems.
Books: Hael, Port and Stone
Lectures: Strict Attendance policy, teaching on blackboard
Lectures: Strict Attendance policy, teaching on blackboard
Assignments: Strong emphasis on proofs and theory. Numerical problems were easy. Problems required rigorous proofs and justification
Advanced Follow-up Courses: SI402 Statistical Inference, SI404 Applied Stochastic Processes, SI527 Introduction to derivative pricing
Pro Tips: Heavy focus on abstract theory of probability. Write proper proofs.
Respondent: Pushkar Mohile
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