Deuxième quadrimestre, 52 heures de théorie et 18 heures d'exercices.

Anglais

Learning outcomes to be attained
1 Is able to relate theory to practice.
2 Can develop a reasoning that corresponds to the (domain-specific) scientific requirements.
3 Can identify, model and analyse the results of a discipline-related problem.
4 Knows the techniques and methods of research and knows how to implement them adequately.
5 Supports the conclusions in a scientifically-based discourse.
6 Integrates information technology to come to solutions.
7 Has insight in a basic set of concepts within the domain of mathematics and statistics and their application.
8 Has insight in a basic set of concepts and methods within the domain of operations research, econometrics and multivariate data-analysis and their application.
9 Is able to use mathematical, statistical and research methods in order to set up models for analysing business problems in different domains (natural sciences, technology, economics, business economics,...).
10 Is able to use his knowledge of mathematics, statistics and research methods to judge information and results of business problems in a critical way in different domains (natural sciences, technology, economics, business economics,...).
11 Is able to use ICT-tools as an aid in modelling research problems and in analysing and presenting their results.

Key objectives of the course
1. Use the classical methods to estimate parameters (method of moments, maximum likelihood method).
2. To be able to draw, starting from a sample, conclusions in a scientifal correct way, by constructing confidence statements and/or testing hypotheses.
3. To understand the possibilities and the limitations (assumptions!) of statistical models.
4. The student can read and understand a scientific econometric study.
5. The student can perform a scientific econometric study himself.

Pour le programme de Bachelor of Science in Business Engineering :

Pour le programme de Bachelor of Science in Business Engineering :

Part I : Inferential Statistics
• Estimators and estimations of parameters (Properties of estimators, Method of Moments, Maximum Likelihood Estimator)
• Confidence intervals for one population mean (with s known and unknown)
• Hypothesis testing for one population mean (with s known and unknown)
• Confidence intervals and hypothesis testing for two population means
• Confidence intervals and hypothesis testing for one and two population fractions
• Analysis of Variance (One-way ANOVA)
• Analysis of categorical data (chi-square test)

Part II : Econometrics
• An introduction to econometrics
• The simple linear regression model
• Interval estimation and hypothesis testing (for the simple linear regression model)
• Prediction, Goodness-of-fit, and modeling issues

Cours magistral et séances d'exercices

Type : Exam during the examination period
Description of evaluation : Oral, Written, Practical exam
Type of questions : Open questions
Learning material : List of formulas, Calculator, Computer

Part 1 of the exam consists of exercises (practical and theoretical). The problems are similar to the problems treated during the class, the tutorials, the homeworks. This part is written.

Part 2 consists of a practical exercise with a computer with R.
Formulas: the only formulas that are allowed are the formulas that can be downloaded from Toledo. These formulas should be printed and can -without additional notes - be used during the exam.
The weight of both parts will be indicated on the exam itself.

The evaluation methods for the second chance exam are identical to the first.

Pas de bibliographie recommandée