Courses Bachelor Display 20132014
Course Description  To PDF  

Course title  Quantitative Methods II (EBE)  
Course code  EBC1035  
ECTS credits  6,5  
Assessment  None  
Period 


Level  Intermediate  
Coordinator 
Christian Kerckhoffs For more information: c.kerckhoffs@maastrichtuniversity.nl 

Language of instruction  English  
Goals 
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 independentsamples ttest, the pairedsample ttest, onewayANOVA, the chisquare test and regression analysis. 

Description 
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 CobbDouglas 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 reallife data, which will be analysed using EXCEL. 

Literature 
Sydsaeter, Knut, and Peter Hammond (2012), Essential Mathematics for Economic Analysis, 4th ed., Harlow: Pearson Education.
Sharpe, Norean R., De Veaux, Richard D., and Paul F. Velleman (2012): Business Statistics, 2 nd. Intern.ed., New York: Pearson Education International. 

Prerequisites 
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 
