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 using them, analyse suitable random phenomena.
CO2: Understand the concept, properties and important models of continuous random variables and using them, analyse suitable random phenomena.
CO3: Analyse random processes using autocorrelation, power spectrum and Poisson process model as appropriate.
CO4: Compute roots of equations, evaluate definite integrals and perform interpolation on given numerical data using standard numerical techniques
CO5: Apply standard numerical techniques for solving systems of equations, fitting curves on given numerical data and solving ordinary differential equations.
Curriculum
- 2 Sections
- 8 Lessons
- 15 Weeks
- MODULE 1Discrete random variables and their probability distributions, Expectation, mean and variance, Binomial distribution, Poisson distribution, Poisson approximation to the binomial distribution, Discrete bivariate distributions, marginal distributions, Independent random variables, Expectation -multiple random variables4
- Module 2Continuous random variables and their probability distributions, Expectation, mean and variance, Uniform, exponential and normal distributions, Continuous bivariate distributions, marginal distributions, Independent random variables, Expectation (multiple random variables), i. i. d random variables and Central limit theorem (without proof).4
