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Home page > Courses > XXXV cycle > Compulsory Course descriptions XXXV cycle

Compulsory Course descriptions XXXV cycle

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Deepening of Statistics

Programming and data manipulation in R

Computational Statistics

Critical analysis, writing and revision of a scientific article

Criteria for the realisation of a research project

The concept of "principal investigator"

Occupational safety - Biohazard labs*

English (Academic writing)

Elements of Intellectual Property - Patents

Sicurezza – Rischio chimico nei laboratori - Occupational safety- Risk chemical laboratories

** Occupational safety and health course (UniFi)


 

*  Mandatory  to attend at least one of the two courses
** Mandatory  course for all university staff and students to be authorized to carry out reserach and    training activities. The course is partly online and partly in the classroom and takes place in the period November-February of the  first year of the course

 

 

 

Deepening of Statistics


CFU: 7

Docente:

Stefano Benedettelli

Compulsory attendance: 75% of lessons (signature collection)
Final assessment: yes
Course structure: classroom lesson and exercitation
Teaching material: provided  by the teacher

 

Course description

Representation of results through binomial and continuous distribution data tables and graphs. Sample estimate of population parameters.

Precision of estimates, confidence interval. Study of theoretical distributions (Binomial, Poisson, Normal, Chi-square, "t" and "F").

Statistical inference and statistical tests: Chi-square, verification of distributions and contingency tables. “T” test and statistical hypothesis: unilateral and bilateral test, paired data.

Bivariate distributions: analysis of simple regression and correlation. Linear model and multiple regression analysis.

Variance analysis: variance analysis models: fixed; mixed random. Expected components of variance.

Experimental schemes: Factorial distributed in completely randomized and hierarchical blocks (Split-Plot).

Exercises: calculation of the probability of a given event; critical area of ​​acceptance of an event, use of distribution tables, execution of statistical exercises relating to qualitative and quantitative variables. Test of X2, Student's "t" and Fisher's "F". Formulation of the H0 hypotheses and alternative hypothesis. Analysis of the variance of experimental designs with more than two

 

 

Programming and data manipulation in R


CFU: 3

Docenti:

Riccardo Bozzi, Luisa Ghelardini

Compulsory attendance: 75% of lessons (signature collection)
Final assessment: yes
Course structure: classroom lesson and exercitation
Teaching material: provided  by the teacher

 

Course description

The course introduces open source resources for data analysis, and in particular the R environment. In the first part the basics of the R environment are introduced, together with the basic principles of the R code and the available resources for help.

The second part narrows down toward R programming, with a bird’s eye view of the software capabilities.

The third part proceeds toward a more practical introduction, where we will learn through examples on dummy datasets to satisfy the most common needs of data analysis one might find in natural sciences.

In the fourth and last part the student will practice what has been learned by analyzing autonomously some data*2.

The final exam will evaluate the capability of the student to analyze autonomously a dataset.


*1: I dati per questa prova pratica / accertamento finale saranno forniti dall’insegnante. Nel caso il tempo a disposizione sia sufficiente e ce ne sia la possibilità pratica, lo studente può concordare con l’insegnante per l’utilizzo di dati propri.

*2: the dataset for this hands-on / final examination will be provided by the teacher. In case there will be enough time and it will be possible, the student can discuss with the teacher the possibility of using his/her own data.

 

 

Computational Statistics


CFU: 3

Docente:

Federico Mattia Stefanini

Compulsory attendance: 75% of lessons (signature collection)
Final assessment: yes
Course structure: classroom lesson and exercitation
Teaching material: provided by the teacher

 

Course description

The  aims of the course  is  to provide the computational elements required to develop Bayesian statistical models, to program Monte Carlo simulations and to create packages for platform R.

 

Course program

The R software. Frequenciesdistributions, moments, quantiles. Graphical univariate and multivariate summaries. Probability calculus and common random variables: Bernoulli, Binomiale, Normal, Poisson, Multinomial, Beta and Gamma families. Introduction to Bayesian subjective methods. Linear and logistic regression models: estimation and testing with qualitative and/or quantitative explanatory variables. Randomized controlled experiments: random sampling, randomization, control, replication, target and baselines variables.
Requirements: only for PhD students who have already successfully attended the courses of Deepening of  statistics and  Programming and data manipulation in R

 

 

 

Critical analysis, writing and revision of a scientific article


CFU: 1

Docenti:

Giovanni Mastrolonardo      


Compulsory attendance: 75% of lessons (signature collection)
Final assessment: yes
Course structure: classroom lesson and exercitation
Teaching material: provided by the teacher

 

Course description

The course is divided into two distinct parts, which are treated in separate lessons. The first lesson provides to PhD students useful information to learn how to properly "design" scientific communication.

The second lesson introduces PhD students to the control of “scientific quality” through the process of peer-review, a basic exercise to learn to "evaluate" and "being evaluated."

 

 

Criteria for the realisation of a research project


CFU: 2

Docente:

Cristina Vettori

Compulsory attendance: 75% of lessons (signature collection)
Final assessment: yes
Course structure: classroom lesson and exercitation
Teaching material: provided by the teacher

 

Course description

The Course aims to teach graduate students how to write a research proposal. In the Course, the different types of research proposals and the ways in which they can be presented in the context of calls for regional, national and international Programmes will be described.

The basic concepts on how correctly writing a research proposal, addressing all the scientific, organizational and financial issues will be presented.

The criteria used for the evaluation of the proposals by external reviewers will be described and the websites where National and International Funding Agencies and Institutions publish the calls for proposals will be presented.

The course will end with an exercise consisting in writing the PhD project in the form of a research proposal to be submitted in the frame of a call for proposals published by a Regional funding Agency. The project will be evaluated according to the criteria used by the Reviewers of European Projects and this exercise will constitute the final test of the Course.

 

 

The concept of "principal investigator"


Docenti:

Elena Paoletti 

Compulsory attendance: 75% of lessons (signature collection)
Final assessment: yes
Course structure: classroom lesson and exercitation
Teaching material: provided by the teacher

 

Course description

The current research policy in Italy, Europe and USA.

Statistics and metrics on the researchers employment in Italy, Europe and USA.

The principles at the roots of the recent measures for young researchers in Italy and Europe.

The post-doc as principal investigator: writing of the personal career development plan, the mobility, the search for a mentor.

The scientific credit: how to increase it, the appropriate measures to use it.

The role of the principal investigator in the research project.

Useful url link for document download

 

 

Occupational safety - Biohazard labs


CFU: 1

Docente:

Stefano Biricolti

Compulsory attendance: 75% of lessons (signature collection)
Final assessment: yes
Course structure: classroom lesson and laboratory exercitation
Teaching material: provided by the teacher

 

Course description

Definitions and meaning of biosafety: laboratory hazards and risk assessment in manipulating genetically modified organisms (GMOs): good laboratory practices, use of Biological Safety Cabinets, laboratory protocols, contaminated stuff and waste handling.

Ulteriori informazioni sui corsi sulla sicurezza dal sito della Scuola di Agraria

 

 

English (Academic writing)


CFU: 5

Docente: Jessica  Thonn

Frequenza obbligatoria: 75% delle lezioni (raccolta firme)
Accertamento finale:
Attività esercitazionale:
Struttura del corso: lezioni ed esercitazioni
Materiale didattico: text book

The course costs 50 euro

 

Course description

At the end of the course students will be able to:

  • Write about a range of matters;
  • Describe people, objects and processes in Agriculture;
  • Write clear, smooth-flowing, well-structured paragraphs and essays;
  • Adapt their writing to their readers;
  • Adopt a multiple-step writing process;
  • Edit successfully their own and others’ work;
  • Increase grammatical accuracy.

 

 

Elements of Intellectual Property - Patents


Complementary Skills

Docente:

Tessa Pazzini, Federico Rorini

Corso organizzato da UNIFI-CSAVRI organisation

To be defined by the UNIFI-CSAVRI organisation

Compulsory attendance: 75% of lessons (signature collection)
Final assessment: yes
Course structure: classroom lesson
Teaching material: provided by the teacher

 

Course description

Il corso si propone di portare a conoscenza dei dottorandi le opportunità offerte dalla terza missione delle università, quella della valorizzazione e del trasferimento delle conoscenze.

Il corso descriverà il processo di trasferimento tecnologico verso il settore privato dei risultati della ricerca svolta presso le università sviluppando in particolare i temi della brevettazione e degli spin-off.

Verrà introdotto il concetto di gestione della proprietà intellettuale e verranno illustrati i requisiti e la procedura per il deposito di un brevetto di invenzione Obbligatorio per accesso laboratori e attività di campo

Sarà trattato lo strumento degli spin-off (accademici e universitari), descrivendo il ruolo dei facilitatori e l’importanza del piano di impresa.

Verranno presi ad esempio alcuni spin-off nell’ambito delle scienze agrarie sia dell’ateneo fiorentino che di altri atenei.

Ai fini della verifica dell’apprendimento il dottorando dovrà simulare una proposta di spin-off per valorizzare un’idea nell’ambito della tematica  di ricerca svolta nel dottorato.

 

 

Occupational safety- Risk chemical laboratories


Obbligatorio per poter svolgere attività di laboratorio e di campo

CFU: 1

Docente: Ateneo e Regione Toscana
Frequenza obbligatoria: raccolta firme
Accertamento finale:
Esercitazioni:
Struttura del corso:  lezioni on line e dopo esame  ammissione a lezioni in aula
Materiale didattico: sito web UNIFI e fornito dai docenti

 

Course description

Courses are organized periodically by the University and is fosused on health and safety of workers pursuant to the State Regions Agreement of 21.12.2011.
By consulting the indicated website (http://formazionepersonale.unifi.it/) it is possible to identify the chosen date for this type. Compulsory enrollment is required, which will be handled by the Doctorate Coordinator through a written communication to the Training Office (formazionepersonale@unifi.it), in which the names of the persons concerned are given.
Further information on safety courses from the Agricultural School website

 

 
last update: 25-May-2020
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