Course, exercises, code, data, and notebooks

Econometrics — L3

Session 1 introduces covariance, correlation, descriptive evidence, and simple regression. Session 2 develops sampling, probability, estimator distributions and inference, with course and exercise code in Python, R and Stata, notebooks, data and interactive simulators.

Institution
Université Catholique de l’Ouest
Role
Lecture & Tutorial
Level
Undergraduate (L3)
Academic year
2026/2027
Language
French · French-language material

Topics documented in the material

  • Covariance and correlation
  • Simple regression
  • Sampling and probability
  • Estimator distributions and inference
  • Python, R and Stata
  • Notebooks and interactive simulation

Resources

Practical instructions

Session 1 — Covariance, correlation and regression

Course — Python notebook

Jupyter notebook · 27.30 kB

Open resource

Exercises — Python notebook

Jupyter notebook · 9.95 kB

Open resource

Interactive covariance simulator

Interactive HTML · 6.97 kB

Open resource

Complete folder — supports, code, data and supporting checks

ZIP · 1.23 MB

Open resource

Session 2 — Sampling, probability and inference

Course — Python notebook

Jupyter notebook · 34.56 kB

Open resource

Exercises — Python notebook

Jupyter notebook · 11.23 kB

Open resource

Interactive sampling simulator

Interactive HTML · 9.63 kB

Open resource

Complete folder — supports, code, data and supporting checks

ZIP · 1.35 MB

Open resource