ID:
149021-ENG
Dettaglio:
SSD: Statistics
Duration: 48
CFU: 6
Located in:
BERGAMO
Url:
ECONOMICS AND DATA ANALYSIS - 149-270-EN/Data Science Year: 2
Year:
2025
The course is designed to provide knowledge and understanding of contemporary computational methods for solving complex inferential problems. By the end of the course, students will be able to apply existing functions within the R software framework and independently implement new functions and computational techniques tailored to specific inferential challenges across various statistical models.
- Good understanding of probability, inferential statistics, and essential statistical models.
- Fundamental knowledge of the R programming language.
The course consists of a total of 48 hours, combining theoretical lectures (supported by slides) with practical sessions using R software.
The exam includes a practical assessment featuring both theoretical questions and exercises that require the use of the R software. The evaluation will focus also on the ability to critically interpret the results.
- Monte Carlo methods and random number generation: rejection method, importance sampling, inversion method, variance reduction techniques, and numerical integration.
- Numerical and graphical exploration of the likelihood function. Optimization algorithms for conducting frequentist inference in complex scenarios.
- Introduction to resampling techniques such as bootstrap and jackknife, along with bootstrap-based inference for complex models.
- Markov Chain Monte Carlo (MCMC) methods, including the Gibbs sampler and Metropolis-Hastings, with an emphasis on diagnostic techniques and their application in Bayesian inference