EM2206 Statistics and Probability


This course  introduces the student  the concepts of probability and random processes and to their application in  engineering problems



Credit Hours:


Contact Hours:

45 hours of Lectures
15 hours of Assignments/Tutorials

Course Marks

70%  Final Exam
30% Course Work

Text & References

     Probability and Random Processes for Electrical Engineering, 2 nd edition, Alberto Leon-Garcia, Addison-Wesley, 1993, ISBN 0-201-50037-X.
Kreyszig, "Advanced Engineering Mathematics", JohnWiley & Sons, 8th Edition, 1999.
K. A. Stroud, "Engineering Mathematics", ELBS, 4th Edition, 1995. 
K. A. Stroud, "Further Engineering Mathematics", ELBS, 3rd edition, 1996.


Statistic concepts in modern society; frequency distribution, the normal distribution, element of statistical inference, estimation and hypothesis testing, contingency tables, linear regression and correlation, simple analysis of variance. Introduction to the basic Theory of probability and its applications. Basic concepts of probability, random variables, and their distribution functions


Introduction, Definitions 
Set Operations
Probability Introduced
Probability Axioms
Math Model
Joint & Conditional Probability
Independence, Bernoulli Trials
Ran. Variables and Distribution Functions
Density Functions
Gaussian Random Variables 
Other Density Functions
Conditional Probability
Expectation Moments
Transformations of a Random Variables
Vector Random Variables
Joint Distribution & Density
Conditional Distributions, Independence
Sums of Random Variables
Random Processes
Correlation Functions.
Gaussian, Poisson Processes
Elementary sampling Theory for normal population:
Central limit theorem. Statistical inference (point and interval estimation and hypothesis testing) on means, proportions and variances. Power and operating characteristics of tests. Chi-squares test of goodness of fit. Simple linear regressions.