Oman College of Management & Technology
Department of Computer Science
Baraka, Oman
Tel. (968) 26893366
Fax (968) 26893068
(502104) Probability
Class sections and Lecturers:
Section 1: 8:30 - 10 Mon and Wed C5
Loay AlNeamy
Instructors Office Hours:
Email:
Office Location:
Office Hours:
Website:
Loay.alneimy@omancollege.edu.om
223
Sun, Tue, Thu 10:30-11:30, 13:30-14:30
Mon, Wed 10:00 – 11:30
www.omancollege.edu.om/loay
Course Code : 502104
Course Name : Probability
Semester / Session : First 2015/2016
Credit Hours : 3 Hrs
Course Prerequisites : -
Course Description
The course covers the basic principles of the theory of probability and its applications. Topics include
combinatorial analysis used in computing probabilities, the axioms of probability, conditional
probability and independence of events; discrete and continuous random variables; joint, marginal, and
conditional densities, moment generating function; laws of large numbers; binomial, Poisson, gamma,
univariate, and bivariate normal distributions.
Course objectives
 Know the definitions of permutations, combinations, distinguishable permuations, the hypergeometric
distribution, Bernoulli trials, and the Binomial distribution.
 Know the "formal definitions" of Probability, conditional probability, mutually independent events, random
variable, and the probability mass function of a random variable.
 Know the statement of the Multiplication Principle, the Multiplication Rule for probabilities, and Bayes'
Theorem.
 Know how to prove properties of probability (e.g. P(A B) = P(A) +P(B) - P(A B), ...), Bayes' Theorem,
properties of independence.
 Finally, be able to compute using enumeration techniques and apply them to probabilities and random
variables.
 Be able to compute probabilities for joint probability distributions.
 Be able to compute marginal and conditional distributions, correlation coefficients, and expectations for
random variables with joint distributions.
 Know the properties of independent random variables.
Learning Outcomes
After completing this course the student should be able to:
 Set functions including set notation and basic elements of probability
 Mutually exclusive events
 Addition and multiplication rules
 Independence of events
 Combinatorial probability
 Conditional probability
 Bayes Theorem / Law of total probability
Teaching Methods
The course will be based on the following teaching and learning activities:
 Power point presentations that covers the theoretical part
 Review questions
 Lab sessions
Course Plan
Course Time Table:
Week
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
Subjects
Empirical and probability distribution
Continuous-type data
Time sequences
Probability density and mass functions
Properties of probability
Methods of enumeration (First Exam)
Conditional probability
Independent events
Bayes' theorem
Discrete distribution
Random variables of the discrete type (Second exam)
The poisson distribution
Random variables of the continuous type
The uniform and exponent ional distribution
The normal distribution
Final Exam
Evaluation Plan
Modes Of Assessment
First Exam
Second Exam
Assignments
Final Exam
Score
20%
20%
10%
50%
* Makeup exams will be offered for valid reasons only. Makeup exams may be different from regular exams in content and
format.
Attendance Policy
Lecture attendance is mandatory. Students are allowed maximally of 15% absentia of the total module
hours.
Teaching Resources
Main Textbook : Probability and Statistical Inference (6th Ed.), by R. V. Hogg and E. A. Tanis, Prentice-Hall,
2001. ISBN: 0-13-027294-9
Recommended Books:
Fundamentals of Applied Probability Theory, Drake.