Descriptif
- Basics on statistics and probability
- Derivatives and integrals (revision)
- Some basics on correlation and causation
- Inferential statistics (population and sample, Weak Law of Large Numbers, Central Limit Theory)
- Descriptive statistics (measures of central tendency, measures of variation, percentiles…)
- Experiments, conditional probabilities, random variables, probability density functions for continuous and discrete random variables, characteristics of probability distributions
- Introduction to estimation (unbiasedness, efficiency, consistency)
- Exercises
- Introduction to econometrics
- What is an econometric model? Variables, parameters
- Linear models and basic assumptions
- Exercises
- R coding
- Installing R and Rstudio
- R environment and packages
- R coding (functions, vectors, dataframes)
- Importing and exporting data
- Data management
- Basic data analysis
- Graphics
- Exercises
Diplôme(s) concerné(s)
Parcours de rattachement
Format des notes
Numérique sur 20Littérale/grade réduitPour les étudiants du diplôme Economics, Data Analytics and Corporate Finance
Le rattrapage est autorisé (Note de rattrapage conservée)Pour les étudiants du diplôme Economics for Smart Cities and Climate Policy
Le rattrapage est autorisé (Note de rattrapage conservée)Pour les étudiants du diplôme Echanges PEI
Le rattrapage est autorisé (Note de rattrapage conservée)- Crédits ECTS acquis : 5 ECTS