| 1 | Lecture-01-Basic principles of counting | PDF unavailable |
| 2 | Lecture-02-Sample space , events, axioms of probability | PDF unavailable |
| 3 | Lecture-03-Conditional probability, Independence of events. | PDF unavailable |
| 4 | Lecture-04-Random variables, cumulative density function, expected value | PDF unavailable |
| 5 | Lecture-05-Discrete random variables and their distributions | PDF unavailable |
| 6 | Lecture-06-Discrete random variables and their distributions | PDF unavailable |
| 7 | Lecture-07-Discrete random variables and their distributions | PDF unavailable |
| 8 | Lecture-08-Continuous random variables and their distributions. | PDF unavailable |
| 9 | Lecture-09-Continuous random variables and their distributions. | PDF unavailable |
| 10 | Lecture-10-Continuous random variables and their distributions. | PDF unavailable |
| 11 | Lecture-11-Function of random variables, Momement generating function | PDF unavailable |
| 12 | Lecture-12-Jointly distributed random variables, Independent r. v. and their sums | PDF unavailable |
| 13 | Lecture-13-Independent r. v. and their sums. | PDF unavailable |
| 14 | Lecture-14-Chi – square r. v., sums of independent normal r. v., Conditional distr. | PDF unavailable |
| 15 | Lecture-15 Conditional disti, Joint distr. of functions of r. v., Order statistics | PDF unavailable |
| 16 | Lecture-16-Order statistics, Covariance and correlation. | PDF unavailable |
| 17 | Lecture-17-Covariance, Correlation, Cauchy- Schwarz inequalities, Conditional expectation. | PDF unavailable |
| 18 | Lecture-18-Conditional expectation, Best linear predictor | PDF unavailable |
| 19 | Lecture-19-Inequalities and bounds. | PDF unavailable |
| 20 | Lecture-20-Convergence and limit theorems | PDF unavailable |
| 21 | Lecture-21-Central limit theorem | PDF unavailable |
| 22 | Lecture-22-Applications of central limit theorem | PDF unavailable |
| 23 | Lecture-23-Strong law of large numbers, Joint mgf. | PDF unavailable |
| 24 | Lecture-24-Convolutions | PDF unavailable |
| 25 | Lecture-25-Stochastic processes: Markov process. | PDF unavailable |
| 26 | Lecture-26-Transition and state probabilities. | PDF unavailable |
| 27 | Lecture-27-State prob., First passage and First return prob | PDF unavailable |
| 28 | Lecture-28-First passage and First return prob. Classification of states. | PDF unavailable |
| 29 | Lecture-29-Random walk, periodic and null states. | PDF unavailable |
| 30 | Lecture-30-Reducible Markov chains | PDF unavailable |
| 31 | Lecture-31-Time reversible Markov chains | PDF unavailable |
| 32 | Lecture-32-Poisson Processes | PDF unavailable |
| 33 | Lecture-33-Inter-arrival times, Properties of Poisson processes | PDF unavailable |
| 34 | Lecture-34-Queuing Models: M/M/I, Birth and death process, Little’s formulae | PDF unavailable |
| 35 | Lecture-35-Analysis of L, Lq ,W and Wq , M/M/S model | PDF unavailable |
| 36 | Lecture-36-M/M/S , M/M/I/K models | PDF unavailable |
| 37 | Lecture-37-M/M/I/K and M/M/S/K models | PDF unavailable |
| 38 | Lecture-38-Application to reliability theory failure law | PDF unavailable |
| 39 | Lecture-39-Exponential failure law, Weibull law | PDF unavailable |
| 40 | Lecture-40-Reliability of systems | PDF unavailable |