Probability and Random Variables

Programming for AIHours: 3 0 3

Probability, joint and conditional probability, Bayes theorem, random variable, distribution and density functions, the Gaussian random variable, expectation, moments, transformation of a random variable, multiple random variables, random processes, stationarity and independence, correlation and covariance, power spectral density, coloured and white noise.

Pre-requisites: MT102
Co-requisites: none

Hours: XYZ where X = Lecture, Y = Lab, Z = Credit
All hours are per week.
3 Lab hours constitute 1 credit hour
1 credit hour implies 1 lecture of 50mins per academic week. 16 weeks in total.
Pre-Requisite courses are courses required to be completed before this course may be taken
Co-Requisite courses are courses required to be taken along with this course

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