Courses Bachelor Display 2015-2016

Course Description To PDF
Course title Quantitative Methods II (EBE)
Course code EBC1034
ECTS credits 6,5
Assessment Whole/Half Grades
Period Start End Mon Tue Wed Thu Fri
4 1-2-2016 1-4-2016 L X/E X/E L
Level Intermediate
Coordinator Christian Kerckhoffs
For more information:
Language of instruction English
Introduction to the matrix representation of (linear) systems of equations, and to the (constrained) maximization or minimization of (nonlinear) functions of more than 1 variable.
Introduction to the basic tools of inferential statistics, a.o. the independent-samples t-test, the paired-sample t-test, one-way-ANOVA, the chi-square test and regression analysis.
QM II continues the quantitative topics that were initiated in QM I: mathematics and statistics. There is no separate formal training in (or testing of) computer science: this element has been integrated into the remaining two parts of the course.

In the mathematics part, we will expand the analysis of functions and (systems of) equations. Issues that will be addressed are:
- The matrix representation of systems of linear equations (so called linear algebra) will be introduced and supplemented by the concepts of determinants and inverse matrices, which are important tools to manipulate such systems.
- The (constrained) maximisation or minimisation of (nonlinear) functions of more than 1 variable. We introduce the extreme value theorem and the Lagrange multiplier method.
- Further topics include implicit differentiation, the Taylor expansion, and a collection of tools often used in finance but also in other fields (buzzwords: interest rates, present value, discounting, and geometric series).
All these topics will be introduced and illustrated using economic or business applications, and functions that are often used in these fields (e.g. the Cobb-Douglas production function) will be analysed extensively.

In the statistics part, we will expand the coverage of inferential statistics, i.e. how to draw conclusions about a population based on a sample. Students will learn to apply the basic tools of inferential statistics (confidence intervals and hypothesis tests) to examine a large array of questions that may occur in economics or business. We will focus on the following topics:
-How to examine whether the mean of some quantitative variable (e.g. income) differs between two or more populations (e.g. men vs. women). Related to this, we will also examine what to do when the data are paired, and when the variable of interest is a proportion.
-How to analyse relationships between qualitative variables (e.g. between brand preference and gender).
-How to analyse relationships between two or more quantitative variables (e.g. between income and age) using regression analysis. This is one of the most frequently used statistical techniques in economics and business.
All these issues will involve the use of real-life data, which will be analysed using EXCEL.
Sydsaeter, Knut, and Peter Hammond (2012), Essential Mathematics for Economic Analysis, 4th ed., Harlow: Pearson Education (subject to change).
Sharpe, Norean D., De Veaux, Richard D., & Velleman, Paul F. (2015), Business Statistics, 3rd ed., New York: Pearson Education International. ISBN-10: 0321925831. ISBN-13: 9780321925831 (subject to change).
Basic knowledge of mathematics and statistics, comparable to the course Quantitative Methods I, code EBC1005/1006/1007.
Teaching methods (indicative; course manual is definitive) PBL / Lecture / Assignment
Assessment methods (indicative; course manual is definitive) Written Exam
Evaluation in previous academic year For the complete evaluation of this course please click "here"
This course belongs to the following programmes / specialisations
Bachelor Economics and Business Economics Year 1 Compulsory Courses