Download Course Objectives: Course Description: Learning

THE UNIVERSITY OF THE WEST INDIES
DEPARTMENT OF ECONOMICS
ECON3031: PROBABILITY AND DISTRIBUTION THEORY
Semester 1, 2014-15
Pre-requisites: ECON 2008, ECON 1006 or MATH 1150 or MATH 1180
Anti-requisites: MATH 2140
Lecturer: Mr. Fabian Vassel
Course Objectives:
The course is aimed at:
o Providing students with a formal treatment of probability theory.
o Equipping students with essential tools for statistical analyses at the graduate level.
o Fostering understanding through real-world statistical applications.
Course Description:
The course explores the basic concepts of modern probability theory and its applications for
decision-making 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.
Learning Outcomes
At the end of the course students should be able to:
o Develop problem-solving techniques needed to accurately calculate probabilities.
o Apply problem-solving techniques to solving real-world events.
o Apply selected probability distributions to solve problems.
o Present the analysis of derived statistics to all audiences.
Modes of Delivery
There will be 1 hour of tutorial and 2 hours of lectures per week
Assessment
Mid-semester test: 30%
Quiz: 20%
Final Examination: 50%
Syllabus
1. Probability Concepts
o Definitions of probability
o Axioms & Rules of Probability
o Marginal, Joint & Conditional Probability
o Bayes' Theorem
II. Probability Distribution & Probability Density Functions
o Discrete Random Variables & their Probability
Distributions
o Continuous Random Variables & their Probability
Distributions
o Bivariate and trivariate Distributions
o Marginal & Conditional Distributions
III. Mathematical Expectation
o Expected Values of Random Variables
o Moments & their Applications
o Moment Generating Functions
o Conditional expectation
IV. Special Distributions
o Special Discrete Probability Distribution Functions
o Discrete Uniform
o Bernoulli
o Binomial
o Poisson
o Special Continuous Probability Distribution Functions
o Continuous Uniform
o Exponential
Resources
Prescribed:
Miller, I. and Miller, Marylees. John E. Freund’s Mathematical Statistics with Application, 7th ed.,, New
Jersey: Prentice Hall, 2010.
Highly Recommended:
Wackerly, D, Mendenhall, W. and Scheaffer, R. Mathematical Statistics with Applications. Duxbury:
California, United States, 2008.