- Docente: Maroussa Zagoraiou
- Crediti formativi: 6
- SSD: SECS-S/01
- Lingua di insegnamento: Inglese
- Modalità didattica: Convenzionale - Lezioni in presenza
- Campus: Bologna
- Corso: Laurea Magistrale in Statistical Sciences (cod. 9222)
-
dal 10/02/2025 al 13/03/2025
Conoscenze e abilità da conseguire
At the conclusion of this course, students will be familiar with the foundations of experimental design and will be able to: -construct optimal or good designs for a range of experiments -evaluate and compare designs using common optimality criteria -understand the challenges and potential practical problems in the implementation of optimal designs -describe advantages and disadvantages of different designs. Examples from several fields will be provided to show the wide applicability of the optimal design techniques.
Contenuti
Statistical experiments and the role of the design: outcomes (primary endpoints), factors and their levels.
Fundamental principles: randomization, replication and blocking.
Design of Experiments with one factor:
- constant (to determine the sample size);
- dichotomous (balance and Neyman allocation);
- polytomous (analysis of variance)
- quantitative (linear regression and factorial design with two levels)
Design of Experiments with two (or more factors): factorial designs
Optimal design theory
-continuous and exact designs
-the general equivalence theorem
-criteria of optimality: A- optimality, D-optimality and C-optimality
-brief mention on the sequential construction of optimal designs.
Testi/Bibliografia
A. C. Atkinson, A. N. Donev e R. D. Tobias (2007). Optimum Experimental Designs, with SAS. Oxford Statistical Science Series 34.
Slides and exercises will be available on the platform "Virtual learning environment".
Metodi didattici
Traditional lectures
Lecture attendance is not compulsory but is strongly recommended.
(https://corsi.unibo.it/2cycle/StatisticalSciences/lecture-attendance).
Modalità di verifica e valutazione dell'apprendimento
Oral examination at the end of the course.
Grading scale:
<18 fail
18-23 pass
24-26 satisfactory
27-28 good
29-30 very good
30 cum laude excellent
Students can reject the grade obtained at the exam. To this end, they must send a written communication via e-mail to the lecturer.
Strumenti a supporto della didattica
Additional teaching material useful for the preparation of the exam will be available on the platform "Virtual learning environment" of the University of Bologna.
Orario di ricevimento
Consulta il sito web di Maroussa Zagoraiou
SDGs

L'insegnamento contribuisce al perseguimento degli Obiettivi di Sviluppo Sostenibile dell'Agenda 2030 dell'ONU.