Academic Year 2022-2023



Luigi Pace
Unit Credits
Teaching Period
Second Period
Course Type
Prerequisites. Statistica I.
Teaching Methods. Frontal lectures.
Verification of Learning. Written and oral examination.
The student is expected to be able to use likelihood-based frequentist statistical methods to analyze data arising mainly in scientific and technological contexts and to communicate her/his findings both in technical and non-technical language.
The course is an introduction to bivariate and multivariate statistical modeling and to likelihood-based frequentist inference.

Specific contents: review of bivariate and multivariate distributions and density functions;

linear regression models;

simple examples of tests of hypotheses, null and alternative hypotheses, critical regions, size, power, type I and type II errors, Neyman–Pearson lemma; uniformly most powerful tests;

significance level; relation with confidence regions; likelihood-based frequentist inference procedures; their first-order asymptotic theory; higher-order resuls; stimating equations.

Pace L. e Salvan A., Introduzione alla Statistica – II. Inferenza, Verosimiglianza, Modelli, CEDAM, Padova, 2001.

Salvan, A., Sartori, N., Pace, L., Modelli Lineari Generalizzati, Springer-Verlag Italia, Milano, 2020.

Pace, L., Salvan A., Sartori N., Statistical Inference: Theory and Methods, 2023 (in preparation)