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

Prof. Felice Adinolfi

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.

Prof. Nicoletta Mauri

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.

Prof. Alessandro Gesuato

Readings/Bibliography

The teaching materials are available on the Virtual Platform (https://virtuale.unibo.it/).

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

Students must take a written and oral exam for each module that makes up the Integrated Course. The timing and methods (ongoing assessments or a single final exam) will be agreed upon with students during the academic year in order to facilitate the process.

 

As a rule:

The assessment of learning for the Integrated Course ‘MATHEMATICS, STATISTICS AND PHYSICS’ consists of three parts:

• The first part tests knowledge of statistics
• The second part tests knowledge of mathematics
• The third part tests knowledge of physics

WRITTEN TEST FOR EACH MODULE:

• test consisting of 10 theoretical questions worth 2 points and 2 exercises worth 6 points
• No support materials are allowed during the test, but the use of devices such as calculators is permitted.
• The written test will be published within 5 working days on the virtual platform (https://virtuale.unibo.it/ ) of the lecturer who conducted the test.ORAL TEST:
• In assessing the oral exam, the lecturer will refer to the following learning assessment scale:- Preparation on a very limited number of topics covered in the course and analytical skills that emerge only with the help of the teacher, expression in generally correct language → 18-22; - Preparation on a limited number of topics covered in the course and independent analytical skills only on purely practical issues, expression in correct language → 23-26;- Preparation on a wide range of topics covered in the course, ability to make independent critical analysis choices, mastery of specific terminology → 27-29;- Substantially comprehensive preparation on the topics covered in the course, ability to make independent critical analysis and connection choices, full mastery of specific terminology and ability to argue and self-reflect → 30-30L.
• The oral exam grade is communicated at the end of the interview. The exam is passed with a minimum grade of 18/30.

The exam is passed if all the required tests are passed and the final grade is the weighted average of the grades obtained in the various parts of the exam, expressed out of 30. A minimum final grade of 18/30 is required.

A negative assessment does not result in a grade being awarded, but only a judgement (withdrawn or rejected) recorded in the electronic report compiled on AlmaEsami, and therefore does not affect the student's career.

The assessments of the individual tests and the final exam grade will be published on the Virtual Platform (https://virtuale.unibo.it/) by the recording lecturer within 5 working days of the exam date.

Students may refuse the grade once, by notifying the recording lecturer by email within 5 working days.

The teacher responsible for this course is Prof. Felice Adinolfi.

Students can register for exam sessions via AlmaEsami (http://almaesami.unibo.it/). Exam sessions are offered during the periods indicated in the academic calendar. Additional exam sessions are reserved for students who have exceeded the standard duration of their studies.

Students with SLDs or temporary or permanent disabilities: please contact the relevant University office (https://site.unibo.it/studenti-con-disabilita-e-dsa/it/per-studenti) in good time. It will be their responsibility to propose any adjustments to the students concerned, which must in any case be submitted 15 days in advance for approval by the lecturer, who will assess their appropriateness in relation to the course objectives.

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