Courses Catalogue

Quantitative Methods

ACADEMIC PROGRAMME: Business Administration (Finance and Accounting), Bachelor
COLLEGE/SCHOOL/FACULTY: College of Economics and Management
PROGRAMME TYPE: Undergraduate

Course Content and Outline

Probability and Distributions

·         The concept of probability.

·         The rules of probability.

·         Addition and multiplication laws of probability.

·         Conditional probabilities, prio and posterior probabilities and expected values. Bayes theorem.

·         Decision trees.

·         Permutations and combinations.

·         The concept of probability distribution.

·         Normal distribution.

Index Numbers

·         Definition, uses, limitations and construction.

·         Computation and interpretation of simple index numbers.

·         Time series relatives.

·         Simple vs weighted averages.

·         Laspeyres and paasche price and quantity indices: computation, comparison and interpretation.

·         Published indices.

Regression and Correlation

·         Regression: Uses, regression line, dependent and independent values, interpolation and extrapolation.

·     Correlation: meaning and purpose; product moment correlation coefficient, coefficient of determination, Spearman’s rank correlation coefficient.

·         Correlation vs. causality.


Forecasting – Time Series Analysis

·         Definition.

·         Types of forecasts.

·         Classification of forecasting techniques

·         Moving averages.

·         Exponential smoothing.

·         Time series components – meaning, computation and interpretation.

Linear Algebra and Calculus

·         Equations – Linear, quadratic and simultaneous.

·         Functions and graphs.

·         Differentiation: role, rules; maximum and minimum points; second derivatives, cost, revenue and profit functions.

Decision Theory

·         Expectation.

·         Decision rules.

·         Decision trees

·         Redundancy.

Linear Programming

·         Definition.

·         Meaning of decision variables, objective function, shadow prices, constraints and feasible region.

·         Formulation of maximization and minimization problems.

·         Graphics LP solution.