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Engineering Probability
Spring 2025

Title
Topic
Lecture 1

Experiments, sample space, events


Lecture 2

Axioms, probabilistic models, counting methods

Lecture 3

Conditional probability

Lecture 4

Baye's rule, independence, Bernoulli trials​

Lecture 5

Discrete random variables

 

Lecture 6

Expected value and moments 

Lecture 7

Conditional probability mass functions

Lecture 8

Cumulative distribution functions

Lecture 9

Probability distribution functions, continuous random variables

Lecture 10

The Gaussian random variable, Q function 

Lecture 11

Expectations of a random variable 

Lecture 12

Functions of a random variable; inequalities

 
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