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.

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.

3° Year  activated in the A.Y. 2024/2025

ModulesCreditsTAFSSD
9
C
AGR/15 ,CHIM/08
1 module among the following
9
C
MED/12 ,MED/13 ,MED/14
1 module among the following
6
C
MED/35
Training
7
F
-
Final exam
4
E
-
activated in the A.Y. 2024/2025
ModulesCreditsTAFSSD
9
C
AGR/15 ,CHIM/08
1 module among the following
9
C
MED/12 ,MED/13 ,MED/14
1 module among the following
6
C
MED/35
Training
7
F
-
Final exam
4
E
-
Modules Credits TAF SSD
Between the years: 2°- 3°

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.




S Placements in companies, public or private institutions and professional associations

Teaching code

4S010589

Credits

6

Language

Italian

Scientific Disciplinary Sector (SSD)

MED/01 - MEDICAL STATISTICS

The teaching is organized as follows:

PARTE 2

Credits

4

Period

1° SEM Scienze nutraceutiche

Academic staff

Lucia Cazzoletti

PARTE 1

Credits

2

Period

1° SEM Scienze nutraceutiche

Academic staff

Giuseppe Verlato

Learning objectives

The course in theoretical and applied Medical Statistics andEpidemiology aims at providing students with basic statistical knowledge, necessary to correctly interpret quantitative data from groups of individuals, by separating general mathematical laws from inter-individual variability. For this purpose, the main concepts of descriptive statistics, probability theory and inferential statistics will be presented, along with the main elements of descriptive, analytic and evaluative epidemiology. The illustration of statistical and epidemiological theory will be integrated with computer practice, where students will be asked to solve simple exercises by using a spreadsheet or freely available simple statistical software. Statistical and epidemiological methods will be applied to the health sciences, with particular focus on human nutrition. On completion of the course, the student should be able to appropriately describe the information collected on a group of patients, generalize the information provided by a sample to the source population, estimate disease frequency in human populations and evaluate related risk factors, particularly in the nutritional field.

Examination methods The exam consists of a written verification also with exercises of the level of knowledge on the course topics.
To pass the exam, students will have to prove their understanding of basic statistical and epidemiological concepts. In addition, students will be asked to solve simple exercises in the nutritional field, by applying statistical-epidemiological methods. Students will be asked not only to correctly perform.

Prerequisites and basic notions

The student should have basic knowledge of mathematics, which has already been the subject of the admission test. In particular, the student should have basic knowledge of algebra, including equations and functions, and geometry.

Program

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UL: PARTE 1
------------------------
INTRODUCTION: The role of Statistics in Health Professions.
DESCRIPTIVE STATISTICS: Different measurement scales – Statistical variables and their presentation through frequency distributions: one-entry or double-entry tables – Measures of central tendency: mean (arithmetic, geometric, weighted), median, mode, percentiles – Measures of dispersion: range, interquartile range, sum of squares, variance (mean square), standard deviation, variation coefficient.
PROBABILITY: Classic, frequentist, subjective interpretations of probability – Sum and product rules of probability – Independent and dependent events and conditional probability – Sensitivity, specificity, positive and negative predictive value of a diagnostic test – ROC curves – Bayes theorem and its application to differential diagnosis
------------------------
UL: PARTE 2
------------------------
The course is divided into theoretical lectures and hands-on sessions using free online worksheets or statistical software.
The main topics that will be presented are:
PROBABILITY: Random variables - Probability distributions of a random variable: normal and binomial distribution - Population and sample; basics of sampling theory - The sampling distribution of an estimator (sample mean).
STATISTICAL INFERENCE: Point and interval estimates: confidence interval - The logic of the hypothesis test: null hypothesis and alternative hypothesis; type I and II error; power of a test - Choice of statistical test.
EPIDEMIOLOGY: The objects of epidemiological research (outcome, occurrence parameter, determinant); Disease frequency measures: prevalence, incidence - Association measures: attributable risk, relative risk, odds ratio - Study design: cross-sectional, cohort and case-control study. Causal interpretation of an empirical association (causal models, random error, bias, confounding). The modification of the measure of effect.
INTRODUCTION TO NUTRITIONAL EPIDEMIOLOGY: Notes on the methods of investigation and statistical analysis used in the field of nutritional epidemiology: use of the Food Frequency Questionnaires; statistical methods for the determination of nutrients and dietary patterns
LABORATORY: health statistics and epidemiology exercises using a free access statistical spreadsheet or software.

Bibliography

Visualizza la bibliografia con Leganto, strumento che il Sistema Bibliotecario mette a disposizione per recuperare i testi in programma d'esame in modo semplice e innovativo.

Didactic methods

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UL: PARTE 1
------------------------
The course will consist of frontal lessons in classroom and exercise on nursing problems. It is mandatory to attend at least 75% of the lessons. Students with a certified illness will be enabled to attend remotely by the zoom platform.
------------------------
UL: PARTE 2
------------------------
The course will consist of frontal lessons in classroom and hands-on exercises utilizing free online spreadsheets or statistical software. It is mandatory to attend at least 75% of the lessons. Students with a certified illness will be enabled to attend remotely by the zoom platform.

Learning assessment procedures

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UL: PARTE 1
------------------------
The written examination will consist of about 20 multiple choice questions with 5-8 possible answers, and one exercise of Descriptive Statistics on a simple data set.
If a new lockdown phase will be enacted, the exam modality will be modified accordingly, i.e. exams will be performed in rooms large enough to guarantee social separation, or exams will be administered using the web-platform Zoom.
------------------------
UL: PARTE 2
------------------------
The test includes a written test with exercises and questions. The final rating is given a score out of thirty.

Students with disabilities or specific learning disorders (SLD), who intend to request the adaptation of the exam, must follow the instructions given HERE

Evaluation criteria

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UL: PARTE 1
------------------------
The exam will evaluate not only the acquisition of statistical knowledge, but also the ability to adopt it critically to solve health problems. One point will be awarded for each correct answer, and zero points for incorrect or missing answers.
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UL: PARTE 2
------------------------
The ability to critically apply statistical knowledge to address health issues will also be assessed, in addition to the acquisition of such knowledge.

Criteria for the composition of the final grade

The final grade will be the weighted average of the grade obtained for parts 1 and 2 of the course, with weights of the credits of the 2 parts (2 credits for part 1 and 4 credits for part 2).

Exam language

------------------------ UL: PARTE 1 ------------------------ italiano ------------------------ UL: PARTE 2 ------------------------ Italiano