Course Information

Course Name	Turkish	Uygulamalı Olasılık ve Olasılığa Dayalı Sistem Çözümlemesi
	English	Applied Probability and Probabilistic System Analysis
Course Code	BLU 623E	Credit	Lecture (hour/week)	Recitation (hour/week)	Laboratory (hour/week)
Semester	-	3	3	-	-
Course Language		English
Course Coordinator		Behçet Uğur Töreyin Behçet Uğur Töreyin
Course Objectives		1) To teach fundamentals of probability theory. 2) To teach applications of probability theory in informatics.
Course Description		Introduction to Probabilistic Modeling, Conditional Probability, Combinatorics. Discrete Random Variables, Extension to higher dimensions. Continuous Random Variables, Extension to higher dimensions. Derived Distributions; Convolution, Covariance, Correlation. Sums of a random number of random variables. Prediction, Estimation, Convergence in Probability. Signal-to-Noise Ratio. Random Processes (Bernoulli, Poisson, Gaussian), Markov Chains. Laws of Large Numbers. Bayesian Inference. Hypothesis Testing. Applications on Queueing Theory. Applications on Statistical Learning
Course Outcomes		Students who pass the course will have knowledge about: 1) Fundamentals of probability theory, 2) Common random processes, 3) Probabilistic Systems Analysis, 4) Applications of probability theory
Pre-requisite(s)		-
Required Facilities		-
Other		-
Textbook		[1] Bertsekas, Dimitri, and John Tsitsiklis. Introduction to Probability. Athena Scientific, 2008. [2] Roy D. Yates, David J. Goodman, Probability and Stochastic Processes: A Friendly Introduction for Electrical and Computer Engineers, Wiley, 1999. [3] Steven M. Kay, Intuitive Probability and Random Processes using MATLAB, Kluwer Academic Publishing, 2006. [4] Athanasios Papoulis, S. Unnikrishna Pillai, Probability, Random Variables and Stochastic Processes (Fourth Edition) McGraw-Hill, 2002. [5] Alberto Leon-Garcia, Probability, Statistics, and Random Processes for Electrical Engineering (Third Edition), Pearson-Prentice Hall, 2008.
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