Probability and Discrete Analysis

Description

An introduction to statistics and statistical analysis on data observation – Statistical measurements – Elementary Probability – Probability theorems – Conditional probability – Independent and dependent events –Total probability rule – Baye’s Theorem and applications – Discrete probability distribution – probability mass function – Continuous probability distribution – probability density function. Mathematical expectation, mean and variance – Special discrete distribution: Bernoulli, Binomial, Hypergeometric and Poisson distributions – Special continuous distribution: Uniform and exponential distribution – Special continuous distribution: normal distribution – The z-transform: definition– properties – The z￾transform: convolution – Inverse z-transform and difference equation– Numerical integration and differentiation.

Program

Bachelor Degree in Electrical and Control Engineering (160)

Objectives

• To give student general information about the concept of probability and statistics and to define the z-transform and their properties. Provide an understanding of the Numerical integration and differentiation to solve real life problems.