Solve problems about the results of random experiments using the concept
of discrete and continuous random variables
Use the concept of joint probability distributions, marginal
distributions and conditional distributions for multiple random variables
for solving complex problems in various engineering domains that involve
probability
Calculate and grasp the significance of the expected value, variance, and
standard deviation of a single random variable and mean vector and
covariance matrix of a random vector
Analyze random processes and characterize the response of LTI systems
driven by a stationary random process using autocorrelation and power
spectral density functions
Gain sufficient background for the subject areas of detection and
estimation, communications, random signal processing, stochastic control,
pattern recognition and machine learning