LM in Data Science

STATISTICAL METHODS IN DATA SCIENCE AND LABORATORY I

In this course we will review the basics of stat & prob (+ going a bit further!) with the aim at providing the fundamentals tools for:

  • setting up a suitable probabilistic model;
  • understanding the principles behind the main inferential problems: estimation, testing, model checking and forecasting, uncertainty quantification;
  • implementing inference on observed data through the likelihood function using both optimization and simulation-based approximations (e.g. resampling, bootstrap, Monte Carlo ecc.)
  • developing statistical computations within a suitable software environment (mainly R)