65965 - Mathematics, Statistics and Physics

Learning outcomes

‘The student learns the main methods and basic tools proper to the quantitative study of collective phenomena. In particular, the student is able to: interpret and critically evaluate information of a statistical nature (reading and understanding articles in journals and/or specialised publications); autonomously produce and process statistical data; apply some of the tools of statistical methodology for the description and quantitative study of phenomena of biological and economic interest. At the end of the course, the student is able to work with real numbers, knows algebraic calculus and the fundamental properties of functions of a real variable. In particular, the student is able to: -use mathematical knowledge and technical tools to a good level; -set up and solve problems; -assimilate new concepts based on experience and previous knowledge. At the end of the course, the student is able to work with vectors and solve simple kinematic exercises, correctly identifying types of motion and knowing how to read a graph. He can solve exercises to determine the equilibrium of rigid bodies and knows the main differences between the various forms of energy and work. In particular, he knows the main laws of hydrostatics and thermodynamics and can solve medium-complex exercises on these topics. In particular, the student is able to - use physical and mathematical knowledge and tools to a good level; - set up and solve problems; - assimilate new concepts based on experience and previous knowledge. He/she will also be able to cooperate with colleagues and reflect on the applications that the laws of physics have in the field of aquaculture, referring to case studies and concrete examples. He will also be able to report on the same topics using technical language specific to the discipline'.

Course contents

Statistics Module:
Historical background and general definitions
Statistics in Applied Research
Definitions: Population, sample, unit
Statistical surveys
Types of variables and data
Data analysis: statistical indicators (measures of central tendency, dispersion)
Definitions of Probability
Distributions (Binomial, Multinomial, Gauss or Normal, Pearson's χ2 distribution, Student's T distribution, Fisher's F distribution)
Simple Linear Regression
Correlation
Mathematics Module
Contents
- Main numerical sets and operations defined in them;
- recollections of algebraic calculus;
- definition of functions and their general properties;
- exponentials, logarithms and trigonometric functions;
- limits and algebra of limits;
- continuity of a function;
- derivatives;
- function study.
Physics module (The course participates in the University's teaching innovation project)
Contents
- main elements of vector calculus;
- kinematics: the main motions;
- dynamics and equilibrium of bodies;
- energy and work;
- hydrostatics: the fundamental laws and exercises;
- thermodynamics: the principles of thermodynamics, thermal expansion, the concepts of heat, internal energy and work; exercises on specific heat and heat capacity.

Readings/Bibliography

Lecture handouts and slides

Teaching methods

Frontal teaching
For the Physics module: Teaching participates in the University's teaching innovation project
Participatory teaching methods.
1) During lectures, students are constantly called upon to apply statistical concepts through coordinated exercises
2) At least once during the course (intermediate or final part), a participative review session is carried out during which students are urged to recall the topics covered, structure them according to logical criteria, identify functional links between concepts and analytical schemes.
In the case of remote teaching, this activity may be replaced by intermediate tests based on multiple-choice questions.
Students with special needs are invited to contact the lecturers of the various modules by e-mail in order to illustrate them and to organise teaching and the conduct of the examinations in the best possible way.

Assessment methods

The student must take a written and oral examination for each module making up the Integrated Course. The timing and methods (in itinere or single final examination) will be agreed with the students during the A.A. in order to facilitate their progress.

As a rule:
GRADING GRID (ORAL EXAMINATION)

A very thorough knowledge of the topics dealt with in the course, together with a high level of critical analysis and liaison skills and a sure command of the specific terminology will be assessed with a maximum mark (30-30L).
A thorough knowledge of the topics addressed in the course, together with good analytical and critical skills and a secure command of the specific terminology will be assessed with good marks (27-29).
A technically adequate preparation and sufficient, though not particularly articulate, capacity for analysis, expressed in correct language, will produce fair grades (23-26).
Sufficient preparation and ability to analyse, expressed in barely formally correct language, will result in sufficiency (18-22).

The student has the right to reject the proposed grade even if it is positive (University Teaching Regulations ART. 16, paragraph 5).

ASSESSMENT OF STUDENTS WITH SPECIAL EDUCATIONAL NEEDS

Particular attention will be paid to the assessment of students certified in accordance with Law 104/90 and Law 170/2010, or students recognised as having special educational needs. These students should contact the teacher by e-mail, (cc the staff of the central office for students with disabilities or with university SLD (https://site.unibo.it/studenti-con-disabilita-e-dsa/it ). The person responsible for this service in our Department is Dr Fabiana Trombetti.

Teaching tools

Slide projection
Analysis of case studies
Exercises and tests on dedicated platforms and Excel
The course slides are accessible on the VIRTUAL system. Students are invited to contact the lecturer by email to report any problems with the access, organisation or content of the published materials.

Office hours

See the website of Felice Adinolfi

See the website of Nicoletta Mauri

See the website of Alessandro Gesuato