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Course Detail

Course Name Probability and Random Processes
Course Code 15MAT213
Program B. Tech. in Computer Science and Engineering, B. Tech. in Electronics and Communication Engineering
Semester Four
Year Taught 2019


Unit 1

Review of probability concepts – conditional probability – Bayes theorem

Random Variable and Distributions: Introduction to random variable – discrete and continuous random variables and its distribution functions – mathematical expectations – moment generating function and characteristic function – Binomial, Poisson, Geometric, Uniform, Exponential, Normal distribution functions (moment generating function, mean, variance and simple problems) – Chebyshev’s theorem.

Unit 2

Random processes: General concepts and definitions – stationarity in random processes – strict sense and wide sense stationary processes – autocorrelation and properties – special processes – Poisson points, Poisson and Gaussian processes and properties.

Unit 3

Systems with stochastic inputs – power spectrum- spectrum estimation, ergodicity –Markov process and Markov chain, transition probabilities, Chapman Kolmogrov theorem, limiting distributions classification of states.

Text Books

  1. Douglas C. Montgomery and George C. Runger, Applied Statistics and Probability for Engineers, (2005) John Wiley and Sons Inc.
  2. A. Papoulis, and Unnikrishna Pillai, “Probability, Random Variables and Stochastic Processes”, Fourth Edition, McGraw Hill, 2002.


  • J. Ravichandran, “Probability and Random Processes for Engineers”, First Edition, IK International, 2015
  • Scott L. Miller, Donald G. Childers, “Probability and Random Processes”, Academic press, 2012.

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