The course explores the basic concepts of modern probability theory and its applications for decisionmaking in economics, business, and other fields of social sciences. Our everyday lives, as well as economic and business activities, are full of uncertainties and probability and distribution theory offer useful techniques for quantifying these uncertainties. The course is heavily oriented towards the formulation of mathematical concepts on probability and probability distributions and densities with practical applications.
Course Objectives:
The course is aimed at:
 Providing students with a formal treatment of probability theory.
 To introduce the students to the fundamentals of probability theory and present techniques and basic results of the theory and illustrate these concepts with applications.
 Fostering understanding through realworld statistical applications.
Learning Outcomes
At the end of the course students should be able to:
 Develop problemsolving techniques needed to accurately calculate probabilities.
 Apply problemsolving techniques to solving realworld events.
 Apply selected probability distributions to solve problems.
 Present the analysis of derived statistics to all audiences.
Contents
 Finite probability spaces
 Basic concept, probability and related frequency
 Combination of events, examples,
 Independence, random variables, expected value
 Standard deviation and Chebyshev's inequality
 Independence of random variables
 Multiplicatively of the expected value
 Additivity of the variance
 Discrete probability distribution.Probability as a continuous set function
 Sigmaalgebras, examples, continuous random variables,
 Expectation and variance, normal random variables and continuous probability distribution.
 Applications: De MoivreLaplace limit theorem, weak and strong law of large numbers, the central limit theorem, Markov chains and continuous Markov process.
Recommended Books
 M. Capinski, E. Kopp, Measure, Integral and Probability, (SpringerVerlag, 1998.)
2. R. M. Dudley, Real Analysis and Probability, (Cambridge University Press, 2004.)
Suggested Books
 S. Ross, A first Course in Probability Theory, 5th ed., (Prentice Hall, 1998.)
 Robert B. Ash, Basic Probability Theory,( Dover. B, 2008.)
Assesment Criteria
 Sessional: 20 (Assignment 10, Attendance 05, Quiz 05)
 MidTerm Exam: 30
 FinalTerm Exam: 50
Time Table
Day

Time

Regular

Self Support

Monday

11:00 AM to 12:30 PM

12:30 PM to 02:00 PM

Tuesday

11:00 AM to 12:30 PM

12:30 PM to 02:00 PM

Commencement of Classes October 12, 2020
Mid Term Examination December 1418, 2020
Final Term Examination February 0812, 2021
Declaration of Result February 19, 2021