Studying at the University of Verona
Here you can find information on the organisational aspects of the Programme, lecture timetables, learning activities and useful contact details for your time at the University, from enrolment to graduation.
Academic calendar
The academic calendar shows the deadlines and scheduled events that are relevant to students, teaching and technical-administrative staff of the University. Public holidays and University closures are also indicated. The academic year normally begins on 1 October each year and ends on 30 September of the following year.
Course calendar
The Academic Calendar sets out the degree programme lecture and exam timetables, as well as the relevant university closure dates..
Period | From | To |
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I semestre | Oct 1, 2018 | Jan 31, 2019 |
I semestre - 3° anno | Oct 29, 2018 | Jan 31, 2019 |
II semestre | Mar 4, 2019 | Jun 14, 2019 |
Session | From | To |
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Sessione invernale d'esame | Feb 1, 2019 | Feb 28, 2019 |
Sessione estiva d'esame | Jun 17, 2019 | Jul 31, 2019 |
Sessione autunnale d'esame | Sep 2, 2019 | Sep 30, 2019 |
Session | From | To |
---|---|---|
Sessione di laurea estiva | Jul 19, 2019 | Jul 19, 2019 |
Sessione di laurea autunnale | Nov 22, 2019 | Nov 22, 2019 |
Sessione di laurea invernale | Mar 20, 2020 | Mar 20, 2020 |
Period | From | To |
---|---|---|
Sospensione dell'attività didattica | Nov 2, 2018 | Nov 3, 2018 |
Vacanze di Natale | Dec 24, 2018 | Jan 6, 2019 |
Vacanze di Pasqua | Apr 19, 2019 | Apr 28, 2019 |
Vacanze estive | Aug 5, 2019 | Aug 18, 2019 |
Exam calendar
Exam dates and rounds are managed by the relevant Science and Engineering Teaching and Student Services Unit.
To view all the exam sessions available, please use the Exam dashboard on ESSE3.
If you forgot your login details or have problems logging in, please contact the relevant IT HelpDesk, or check the login details recovery web page.
Academic staff
![Foto Maurizio Boselli, October 19, 2013](https://docs.univr.it/documenti//Persona/foto/foto204145.jpg)
Boselli Maurizio
Sandri Marco
Study Plan
The Study Plan includes all modules, teaching and learning activities that each student will need to undertake during their time at the University.
Please select your Study Plan based on your enrollment year.
1° Year
Modules | Credits | TAF | SSD |
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2° Year activated in the A.Y. 2019/2020
Modules | Credits | TAF | SSD |
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3° Year activated in the A.Y. 2020/2021
Modules | Credits | TAF | SSD |
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Modules | Credits | TAF | SSD |
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Modules | Credits | TAF | SSD |
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Legend | Type of training activity (TTA)
TAF (Type of Educational Activity) All courses and activities are classified into different types of educational activities, indicated by a letter.
Mathematics and statistics (2018/2019)
The teaching is organized as follows:
STATISTICA
Credits
3
Period
II semestre
Academic staff
Marco Sandri
Learning outcomes
Aim of this course of Statistic is to present, both from a theoretical and an empirical point of view, the main methods of univariate and bivariate descriptive statistics for the analysis of qualitative and quantitative data in the context of viticulture and oenology. The educational objectives have been developed with reference to Dublin descriptors, they are consistent with those characterizing the 1st cycle degree program in which the course is inserted and have been defined in coordination with those of Mathematics module, with which it forms a unique course. More specifically, students who successfully complete this course will be able to: - collect, analyze and interpret statistical data, both qualitative and quantitative, and organize results in order to draw conclusions and decide in uncertain situations; - communicate, to experts and non-experts, statistical information and evaluations, also with the help of graphical devices. By means of a gradual learning process, linking the contents of this course with the educational objectives characterizing the 1st cycle degree programs in which the course is inserted, students will acquire the methodological and applied knowledge about the basic concepts of descriptive statistics (statistical ratios, means, variability, inequality/concentration, association, correlation and regression) necessary for the professional training. Aim of the course of Mathematic is to present, both from a theoretical and an empirical point of view, the main methods of calculus and linear algebra. The educational objectives have been developed with reference to Dublin descriptors, they are consistent with those characterizing the 1st cycle degree program in which the course is inserted and have been defined in coordination with those of Statistics module, with which it forms a unique course. More specifically, students who successfully complete this course will be able to: - determine the main characteristics of a function and sketch its graph; - differentiate a function and solve simple geometrical problems; - integrate a function and solve simple geometrical problems; - solve simple differential equations; - calculate matrix determinants and inverse matrix; - solve a linear system. By means of a gradual learning process, linking the contents of this course with the educational objectives characterizing the 1st cycle degree programs in which the course is inserted, students will acquire the methodological and applied knowledge about the basic concepts of Mathematics necessary to prosecute their studies.
Program
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MM: MATEMATICA
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(PREREQUISITES: Algebraic, exponential and logarithmic equalities and inequalities.)
1) Functions. Limits. Continuity.
2) Derivation and differentiation of functions. Rolle's, Lagrange's and de l'Hospital's theorems and their consequences. Applications and examples.
3) Functions and their graphs. Function's graph and linear transformations. Applications to natural sciences.
4) Integration of functions of a single real variable. Applications and examples.
5) Simple examples of differential equations.
6) Linear systems and matrices: determinants, inverse matrix, Applications to natural sciences.
Each topic is discussed both from a theoretical and an empirical point of view, with special focus on applications.
(notes and slides available at link https://app.box.com/s/t2jamq852r8j93qhhxomjy4rmckmh5vy )
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MM: STATISTICA
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1) Introduction to statistical data analysis: approaches and main topics 2) Univariate descriptive statistics: - Dynamic analysis by means of ratios - Frequency distributions - Location indices: Mode, median, percentiles, algebraic means - Heterogeneity and variability and indices: Gini Index, Shannon entropy, range, absolute deviations, standard deviation, variance. 3) Bivariate descriptive statistics: - Joint frequency distributions - Analysis of association - Analysis of mean dependence - Analysis of linear correlation - Simple linear regression Each topic is discussed both from a theoretical and an empirical point of view, with special focus on case studies dealing with problems arising in the context of viticulture and oenology.
Bibliography
Author | Title | Publishing house | Year | ISBN | Notes |
---|---|---|---|---|---|
S. Bernstein and R. Bernstein | Elements of Statistics - Descriptive Statistics and Probability - Schaum’s Outline Series. | McGraw-Hill | 1999 | 0-07-005023-6 |
Examination Methods
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MM: MATEMATICA
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Students are evaluated by means of a written comprehensive examination, composed of exercises and questions. A time of 2 hours is scheduled. The grades are on a scale of 30. Students who attend lessons can decide to divide the exam in two parts, to be done before the class ends. A time of 2 hours is scheduled for each part and the grades are on a scale of 30. In that case, the mark of Mathematics will be calculated as the average of the scores obtained in the two different parts; in the case of a non-integer result, the mark is rounded upward. Rules for defining the final grade of the Mathematics and Statistics course, which summarizes the tests carried out in the two modules: (1) A module is successfully completed if the student achieves a score of at least 15/30. (2) The examination of Mathematics and Statistics shall be passed only if both modules are successfully completed, provided that the average of the two scores, calculated as shown in (3), is not less than 18/30. (3) The final mark is calculated as the average of the scores obtained in the two modules weighted by the number of credits; in the computation of the average, at 30 cum laude obtained in a module is assigned a score of 31; in the case of a non-integer result, the mark is rounded upward; in the case of an average of at least 30, the final mark will be 30 cum laude.
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MM: STATISTICA
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Students (regardless whether or not they attended lessons) are evaluated by means of a written comprehensive examination, composed of exercises and questions. A time of 2 hours is scheduled. The grades are on a scale of 30. Rules for defining the final grade of the Mathematics and Statistics course, which summarizes the tests carried out in the two modules: (1) A module is successfully completed if the student achieves a score of at least 15/30. (2) The examination of Mathematics and Statistics shall be passed only if both modules are successfully completed, provided that the average of the two scores, calculated as shown in (3), is not less than 18/30. (3) The final mark is calculated as the average of the scores obtained in the two modules weighted by the number of credits; in the computation of the average, at 30 cum laude obtained in a module is assigned a score of 31; in the case of a non-integer result, the mark is rounded upward; in the case of an average of at least 30, the final mark will be 30 cum laude.
The exam can be verbalized only after passing the exams related to both modules.
Type D and Type F activities
Modules not yet included
Career prospects
Module/Programme news
News for students
There you will find information, resources and services useful during your time at the University (Student’s exam record, your study plan on ESSE3, Distance Learning courses, university email account, office forms, administrative procedures, etc.). You can log into MyUnivr with your GIA login details: only in this way will you be able to receive notification of all the notices from your teachers and your secretariat via email and also via the Univr app.
Graduation
Attendance modes and venues
As stated in the Didactic Regulations, attendance is compulsory for practical and laboratory exercises (see courses with laboratory in the annex), unless otherwise stipulated by the teaching board.
Attendance at lectures is strongly recommended.
Part-time enrolment is permitted. To find out more, please consult the Part-time enrolment possibilities page.
The course's teaching activities take place in Villa Lebrecht and Villa Eugenia, located in the San Floriano di Valpolicella campus, and may also take place in the other spaces of the Science and Engineering area, which is composed of the buildings of Ca‘ Vignal 1, Ca’ Vignal 2, Ca' Vignal 3 and Piramide, located in the Borgo Roma campus,
Lectures are held in the classrooms of Villa Lebrecht while practical exercises are carried out in the teaching laboratories dedicated to the various activities.
Overview of courses with laboratory.
The attached document specifies the courses, divided by year, that include exercise/laboratory CFUs: for this type of CFU only, attendance is compulsory in order to be admitted to the examination.
Documents
Title | Info File |
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pdf, it, 121 KB, 18/10/23 |