Probability and Statistics-SC215
Instructor: Jaideep Mulherkar
DA-IICT, Gandhinagar
Course description:
Course is a foundational course that prepares students for further courses in engineering, physics and computer science that involve applications of probability theory. The topics to be covered are:
Axiomatic view of probability: Sample spaces, probability measures in equi-probable and non-equi-probable spaces.
Probability distributions: Discrete (Binomial, Poisson, Geometric) and continuous (Uniform, Exponential, Normal) from both theoretical and practical viewpoints, their expectation values and variances and concepts like linearity of expectations with applications.
Joint distributions: Conditional and marginal distributions, measure of correlations of random variables.
Limit theorems in probability: Law of large numbers and Central limit theorem with applications.
Basics of Statistical estimation theory: Biased and unbiased estimators, minimum variance unbiased estimation, point estimation, confidence interval estimation and maximum likelihood estimation.
Prerequisites: None
Textbooks:
A first course in probability, Sheldon Ross, 8th ed., Pearson.
Introduction to Probability, C. Grinsead, L. Snell . Available online
Course Notes:
Grading:
30% each for 2 midterms and 40% for final