79204 - Biometrics and Design of Experiments

Learning outcomes

The aims of this course are to explain the factors of biological variability and fundamental analysis methods in biostatical research.

Course contents

BIOMETRIC

The biometric of human populations. The evolutive meaning of biological variability. Components of biological variability and their probabilistic nature. Statistical and probabilistic laws of genetic inheritance. Statistical foundations of allelic and genotypic population structure. Experimental and observational studies. Genetic epidemiology. Measure of association for qualitative data and corresponding statistic test. Introduction to non parametric tests.

 

Statistical variability and biomedical research. Statistical aspects of the biomedical research. The statistical measure of clinical events. The analysis of the experimental samples. Statistical significance: a discussion of the most used statistical tests. Bayesian approach to the clinical strategy.

 

EXPERIMENTAL DESIGN

Statistical experiments and the role of experimental designs: outcomes, factors and their levels. Fundamental principles: randomization, replication and blocking. Likelihood, ML and OLS estimators, Fisher Information, estimation theory and hypothesis testing. Design of Experiments with one factor:

1. constant (to determine the sample size);
2. dichotomous (balance and Neyman allocation);
3. polytomous (analysis of variance)
4. quantitative (linear regression and factorial design with two levels)

Design of experiments with two or several factors: full and fractional factorial designs. Optimal design theory

Readings/Bibliography

Russel P.J., I-genetica, Edises, 2007

D.C. Montgomery, Progettazione e analisi degli esperimenti, McGraw-Hill, 2005.

 

A.C. Atkinson, A.N. Donev, R.D. Tobias (2007) Optimum Experimental Designs, with SAS. Oxford University Press.

A. Azzalini (2004) Inferenza Statistica: Una Presentazione Basata sul Concetto di Verosimiglianza. Springer.

D.C. Montgomery (2005) Progettazione e analisi degli esperimenti. McGraw-Hill.

Teaching methods

Lectures, problem classes, homework

Experimental Design participate to a project of experimental teaching. This imply that 20 hours are devoted to in-person lectures and 10 hours will be online.

Assessment methods

The exam aims at testing the student's achievement of the learning outcomes related to the knowledge of the basic tool for the analysis of the genetic and environmental variability of biometric characters, for the statistical analysis of biomedical data, the knowledge of the design of experiments methodology and the ability to design factorial experiments in practical cases.

The oral exam for the Biometrics module focuses on questions concerning topics described and discussed during the lectures.

The exam for the Design of the Experiments module is written, and it contains 2 or 3 exercises to complete in one hour. During the exam it is allowed to consult textbooks or notes.

The overall evaluation is based on the average of the outcome of the Biometrics and Design of the experiments modules and is expressed in marks out of 30. However, the final mark of the course will be awarded only if sufficiency has been reached in each of the two modules.

Teaching tools

Blackboard,PC, Video projector

Office hours

See the website of Rossella Miglio

See the website of Alessandro Baldi Antognini

See the website of Luca Monti