Lecture 1 - Background and Introduction to Probability
Lecture 2 - Axioms of Probability, Conditional Probability
Lecture 3 - Bayes’ Rule, Independence of Events, Probability Laws
Lecture 4 - Random Variables, CDF, PDF, Discrete Random Variables
Lecture 5 - Discrete and Continuous RVs, Gaussian RV, Function of RVs
Lecture 6 - Mean, Variance, Chi-Square Test
Lecture 7 - Multiple Random Variables
Lecture 8 - Conditional Expectation, Functions of Several Random Variables
Lecture 9 - Transformation of RVs, Statistical Properties, Jointly Gaussian RVs
Lecture 10 - Transformation on Gaussian RVs, Sum of RVs, CLT, Intro to Random Processes
Lecture 11 - Statistical Characterization of Random Processes, Sum and Poisson Processes
Lecture 12 - Stationary Random Processes, ACF and PSD, Time Averages
Lecture 13 - Response of Linear Systems, Modulation of Random Signals