Course Objectives
To familiarize students with the foundations of probability and analysis of random processes used in various applications in engineering and science.
- Course Outcomes
At the end of the course students will be able to
CO1: Understand the concept, properties and important models of discrete random variables and to apply in suitable random phenomena.
CO2: Understand the concept, properties and important models of continuous random variables and to apply in suitable random phenomena.
CO3: Familiarize and apply limit theorems and to understand the fundamental characteristics of stochastic processes.
CO4: Solve problems involving Markov Chains, to understand their theoretical foundations and to apply them to model and predict the behavior of various stochastic processes.
- Text Books (T)
- (Text-1) Jay L. Devore, Probability and Statistics for Engineering and the Sciences,9th edition, Cengage Learning, 2016.
- (Text-2) Sheldon M. Ross, Introduction to Probability Models, 13th edition, Academic Press, 2024.
Curriculum
- 4 Sections
- 18 Lessons
- 20 Weeks
- MODULE 1Discrete Probability Distributions7
- MODULE 2Continuous Probability Distributions6
- MODULE 3Stochastic Processes5
- Module 40
