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Course description

Title of the Teaching Unit

Statistique 3 et introduction à l'économétrie

Code of the Teaching Unit

13UMQ11

Academic year

2024 - 2025

Cycle

Number of credits

5

Number of hours

60

Quarter

1

Weighting

Site

Montgomery

Teaching language

French

Teacher in charge

DENDIEVEL Sarah

Objectives and contribution to the program

At the end of the course, the student must have assimilated the basic notions of inference in two or more populations and the study of the possible linear dependence existing between two variables.

These objectives translate into the fact that students must be able to :
- Define and explain the notions of hypothesis testing in two populations.
- Explain the theory of analysis of variance.
- Define and explain the notion of non-parametric tests.
- Define and explain the notion of simple linear regression model.

At the end of this course, the student should be able to :
- Formulate in writing the hypothesis to be tested based on a given problem,
- Choose the appropriate method to test this hypothesis,
- Make the appropriate calculations for this test,
- Interpret in writing the results of the test performed,
- Say in your own words the decision that results from it,
- Identify the possible linear link between two variables,
- Calculate parameter estimates for this linear model and know how to use this linear model to predict possible values of interest.

Prerequisites and corequisites

Mathematics and Statistics II (12 Gesent).
The chapters to be revisited concern more particularly the following notions :
- Point estimation,
- Estimation by confidence interval,
- Hypothesis testing in a single population (averages and proportions).

Content


Teaching methods

The course is given in the form of an ex cathedra course accompanied by practical work sessions.

Assessment method

Written exam.

References

Wonnacott T. H., Wonnacott R.J., Statistique, Economica, 1991.

Droesbeke J.J., Eléments de Statistique, Editions Ellipses, 1994.

Mendenhall W., Beaver R.J., Beaver B.M., A course in business statistics, Duxbury, 1996.

Masson R.D., Lind D.A., Marchal W.G., Statistical techniques in business and economics , Mc Graw-Hill, 1999.

Mc Clave, Benson, Sincich, Statistics for business and economics, Prentice Hall, 1998.

Keller, Warrack, Bartel, Statistics for management and economics, 1990.

Levin, Rubin, Statistics for management, Prentice Hall, 1998.