Unit BIOSTATISTICS FOR INNOVATIVE AND SUSTAINABLE ANIMAL PRODUCTION
- Course
- Animal science
- Study-unit Code
- A003310
- Curriculum
- In all curricula
- Teacher
- Francesca Maria Sarti
- Teachers
-
- Francesca Maria Sarti
- Hours
- 54 ore - Francesca Maria Sarti
- CFU
- 6
- Course Regulation
- Coorte 2023
- Offered
- 2023/24
- Learning activities
- Caratterizzante
- Area
- Discipline zootecniche e delle produzioni animali
- Academic discipline
- AGR/17
- Type of study-unit
- Obbligatorio (Required)
- Type of learning activities
- Attività formativa monodisciplinare
- Language of instruction
- Italian
- Contents
- Biostatistics (union of the words biology and statistics) is the application of statistics to a wide range of topics in biology, but also to network studies generally related to the evaluation of experimental research data. The science of biostatistics includes the formulation of biological experiments and the collection, analysis and interpretation of the results used in animal and environmental sciences and is based on the use of the tools and models of inferential and Bayesian statistics, can also be applied in the field of economics. Therefore, the aim of the course will be the study of the main statistical models used in the field of animal production according to sustainability and their resolution through various computer tools (Excel, R).
- Reference texts
- 1. A. PETRIE, P. WATSON Statistics for Veterinary and Animal Science, Blackwell Science ed., 1999.
2. E. BALLATORI Statistica e metodologia della ricerca, Galeno ed.
3. Commissione di Studio ASPA Metodologia Statistica e Disegno Sperimentale Elementi di Statistica di Base per le Scienze Zootecniche, 2018, EFG.
4. CAMUSSI, F. MOLLER, E. OTTAVIANO, M. SARI GORLA Metodi statistici per la sperimentazione biologica, Zanichelli ed.
5. G.W.SNEDECOR, W.G.COCHRAN Statistical methods, VI edition, Ames, Iowa, USA.
6.R.COCCARDA Manuale di statistica, Statistica descrittiva, inferenziale e calcolo delle probabilità. Maggioli ed.
7. G.A.MACCARARO, B.CHIANDOTTO, R.DE CRISTOFARO, G.CHISCI, F.SALVI, E.OTTAVIANO, E.MARUBINI, M.BABBINI, N.MONTANARO, F.NICOLIS, M.TURRI Biometria principi e metodi, Piccini ed.
8. G. CONTE, C. DI MAURO, N.P.P. MACCIOTTA Elementi di statistica di base per le scienze zootecniche, EFG ed.
9. Lesson’s slide. - Educational objectives
- 1. acquire knowledge on biostatistics 2. acquire knowledge on computer science 3. build an experimental work 4. know the main statistical models 5. know the main statistical software 6. know how to choose the most appropriate model for the type of experiment 7. able to process the results with dedicated software 8. able to interpret the results 9. know how to organize the exposition of the results.
- Prerequisites
- To attend the exam in a profitable way it’s necessary to know the basics of statistics, also it requires good familiarity with the Excel software.
- Teaching methods
- The course is organized as follows: frontal lessons on the topics listed in the program; guided exercises with the computer aid on the topics explained during the course; final exercise with the final written test simulation.
- Other information
- Lecture participation’s is strongly recommended.
- Learning verification modality
- The examination consists in a final written exam lasting about three hours in which students must demonstrate that they can analyze the data using statistical tests explained during the course. The oral exam will test the communication skills of the student with properties of language and the ability to apply the skills acquired.
- Extended program
- THEORETICAL LESSONS
1 Introduction to biostatistics, descriptive statistics and exercises.
2 Matrix algebra and exercises; introduction to R.
3 Non parametric tests and exercises.
4 Parametric tests and exercises.
5 Main statistical models and exercises.
6 Animal experimentation: formulation of experiments and collection, analysis and interpretation of the results used in the various sectors of sustainable animal production.
PRACTICAL LESSONS Resolution of the models studied on the basis of cases applied to sustainable animal production. Model resolution via dedicated software R and Excel. - Obiettivi Agenda 2030 per lo sviluppo sostenibile
- 4. Quality education.