Economics and Management Statistics [ LECGE1224 ]
5.0 crédits ECTS
30.0 h + 15.0 h
2q
| Teacher(s) |
Johannes Jan ;
|
| Language |
French
|
Place
of the course |
Louvain-la-Neuve
|
| Main themes |
Part 1: Basic methods of statistical analysis.
After an introduction to statistical models (population and sampling models), students are shown how statistical sampling distributions form the basis for inferencing. These properties make it possible to check the precision of specific estimators, to construct confidence intervals and to check the risks of error in a hypothesis testing procedure.
Part 2: Application to some standard problems.
In this part, the basic methods taught in Part 1 are adapted to analyzing useful application issues in Economics and Management: Variance analysis (comparison of several averages); inter-variable relation modelling (linear models); Studies of categorical variables including an inter-variable independence test. Students will also be introduced, through simple examples, to the maximum likelihood estimation method, which is particularly useful in the more complex models analysed in later Econometrics courses. We consider finally the problem of poor specification of the model and the case a non-linear regression.
|
| Aims |
The aim of this course is to introduce the types of reasoning and basic methods used in statistical analysis, and examine how they are used to solve simple statistical problems in the field of Economics and Management. This course also aims to teach the core subject-matter developed in the Statistics and Econometrics courses which students will take later in their degree course.
By the end of the course students should be able to understand basic mechanisms of statistical inferencing and provide practical solutions to standard problems of estimation, confidence interval construction and hypothesis-testing on averages, variances and proportions. They should also be able to model inter-variable relations using simple linear regression models, with a basic introduction to multivariate aspects.
|
| Content |
Content :
Statistical model and sampling distribution, point and interval estimation, hypothesis testing, linear model (including matrix rating), Methods of Estimation including Maximum likelihood, Properties estimators, Inference in the simple regression, non linear regression
Method: The course comprises:
- lectures (the teacher introduces the concepts through a particular concrete application and abstracts from that),
- practical exercise sessions (the teacher gives students applications/problems and suggests ways of sol-ving them). Active student participation through reading and independent problem solving
|
| Other information |
Statistics I or equivalent
Course materials : Thomas, R.L.: Modern Econometrics, Pearson Education Ltd., 1997
|
Cycle et année
d'étude |
> Bachelor in Information and Communication
> Bachelor in Philosophy
> Bachelor in Engineering : Architecture
> Bachelor in Computer Science
> Bachelor in Psychology and Education: General
> Bachelor in Economics and Management
> Bachelor in Human and Social Sciences
> Bachelor in Motor skills : General
> Bachelor in Sociology and Anthropology
> Bachelor in Political Sciences: General
> Bachelor in Mathematics
> Bachelor in Biomedicine
> Bachelor in Engineering
> Bachelor in Pharmacy
> Bachelor in Religious Studies
> Preparatory year for Master in Economics: General
> Preparatory year for Master in Management
> Bachelor in Law
|
Faculty or entity
in charge |
> ESPO
|
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