Evidence – Data Science

• Additional material and information will be available at the course web page.

Argomenti del programma: 1. Random variables Review of some basic concepts of probability; the multivariate normal distribution; central limit theory and law of large numbers; statistics and their properties. Statistical models and inference. Examples of statistical models; the problems of statistical inference. Basic tools for estimation and testing statistical hypotheses. Approaches to statistical inference and design issues (16 hours) 2.

• Additional material and information will be available at the course web page.

Argomenti del programma: 1. Random variables Review of some basic concepts of probability; the multivariate normal distribution; central limit theory and law of large numbers; statistics and their properties. Statistical models and inference. Examples of statistical models; the problems of statistical inference. Basic tools for estimation and testing statistical hypotheses. Approaches to statistical inference and design issues (16 hours) 2.

• Additional material and information will be available at the course web page.

Argomenti del programma: 1. Random variables Review of some basic concepts of probability; the multivariate normal distribution; central limit theory and law of large numbers; statistics and their properties. Statistical models and inference. Examples of statistical models; the problems of statistical inference. Basic tools for estimation and testing statistical hypotheses. Approaches to statistical inference and design issues (16 hours) 2.