Probability and Random Variables (650364) ( Syllabus )
Textbook:
"Probability, Random Variables, and Random Signal Principles", Peyton Z. Peebles, 4th edition, McGraw-Hill, Inc, 2001.
References
Probability and Statistics for Engineering and the Sciences (6th Edition), by Jay L. Devore, 2004
Probability and Statistics, Fourth Edition, Murray R. Spiegel, John J. Schiller, R. Alu Srinivasan, Schaum's Outline Series, McGraw-Hill, 2013
Probability, Random Variables, and Stochastic Processes A. Papoulis, 3rd edition, McGraw-Hill, Inc., 1991.
Probability and Stochastic Processes for Engineers Carl W. Helstrom, 2nd edition, Macmillan Pub. Co, 1991
Probability Demystified, Allan G. Bluman, McGraw-Hill, 2005
Mathematical Statistics with Applications, John E. Freund's, Irwin Miller Marylees Miller, Eighth Edition, Pearson 2014
Lectures
Lecture 1: Introduction and Set Theory (pdf)
Lecture 2- Probability Definition, Joint and Conditional Probability (pdf)
Lecture 3- Total Probability, Bayes' Theorem and Independent Events (pdf)
Lecture 4 - Combined Experiments and Bernoulli Trials (pdf)
Lecture 5 - Random Variables-Introduction, Distribution and Density Functions (pdf)
Lecture 6 - Gaussian Random Variable, Other Distribution and Density Types (pdf)
Lecture 7 - Multiple Random Variables (pdf)
Lecture 8 - Mathematical Expectation (pdf)
Lecture 9 - Moments (pdf)
Lecture 10 - Operations on Multiple Random Variables (pdf)
Lecture 11 - Random Processes (pdf)