Course Details

QUANTITATIVE SCIENCES

MS0935

Course
QUANTITATIVE SCIENCES
Code
MS0935
Academic Year
2023/2024
Curriculum Year
2023/2024
Degree Programme
MEDICINE AND SURGERY
Curriculum
000 - CORSO GENERICO
Credits
8
Lecture Hours
66
Scientific Disciplinary Sector (SSD)
MED/42 - General and Applied Hygiene, INF/01 - Computer Science, MED/01 - Medical Statistics
Course Type
Integrated learning activity
Course Delivery
OBB - Obbligatoria
Year
1
Teaching period
Secondo Semestre
Campus
ALESSANDRIA
Teaching language
Italian
Course Contents
The Integrated Course (IC) consists of three disciplines: Epidemiology, Descriptive and inferential statistics, Basic computer science.
Reference Texts
1) Epidemiology: Manuale di epidemiologia per la sanità pubblica, a cura di F. Faggiano; F. Donato; F. Barboneo. Centro Scientifico Editore.
2) Medical statistics: WW. Daniel, CL Cross. Biostatistica, Edises. Altro testo: Triola MM, Triola MF. Fondamenti di Statistica per le discipline biomediche, Pearson
3) Computer science: Curtin, Foley, Sen, Morin, Informatica di base, 6e. McGraw-Hill Education
Learning Outcomes
The transversal educational objectives of the IC consist in defining the principles of epidemiology, the discipline behind the study of the determinants of health and illness of populations, identifying risk factors and protective factors for health, of statistical analysis of epidemiological data and of their organization through databases.
Prerequisites
Basic mathematics for epidemiology and statistics. No specific knowledge is required for Basic computer science.
Teaching Methods
The three IC teachings adopt the following common teaching methods:
Interactive Lectures with presentations in MS-Power Point format (made available to students through DIR), use of tools for student involvement (also through the use of mobile phones), and for self-assessment (quiz on-line with feedback).
Practical lessons and exercises also with the support of the e-learning platform (study in self-learning mode). Some exercises are designed in such a way as to create a link with the other modules of the integrated course.
Video-recorded seminars on topic of interest of Quantitative Sciences (made available to students through DIR).
Additional Information
Specific exercises are planned on the topics covered in each of the CI's teachings.
Students with physical disabilities, Learning Disabilities or Special Education Needs can request specific services and tools via the Staff Sviluppo e Coordinamento Carriere e Servizi alle Studentesse e agli Studenti, consulting the University webpage: https://www.uniupo.it/en/services/services-students-physical-or-learning-disabilities Students with disabilities, learning disabilities or special education needs, once they have contacted the University Staff, can refer to the tutor in charge of the course to define the examination modalities, concerning academic aspects.
Assessment Methods
The three IC teachings adopt the modality of the written exam test. The test is based on closed questions, open questions, calculation exercises and interpretation of the results. To access the written test, the student must pass a practical computer test consisting of exercises and questions made available on the DIR platform. The final grade is determined taking into account the achievement of the expected learning results of all the modules of the integrated course.
Detailed Syllabus
Epidemiology: charactersitcs and aims. Calculation and interpretation of epidemiological measures: prevalence, cumulative incidence, incidence density.
Calculation of: crude rates and interpretation of crude and standardized rates.
Calculation and interpretation of the measures of association and impact (relative risk, odds ratio, attributable risk).
Interpretation of a meta-analysis. Characteristics and conduction of epidemiological studies and gerarchy of scientific evidences: primary and secondary studies, observational and experimental studies. Revies and meta-analysis.
Estimate of the correlation between and within observers (calculation and clinical interpretation of clinical agreement).
Assessing the validity of a diagnostic test (calculation and interpretation of sensitivity, specificity, values predictive of a test).
Frequency distributions and graphical representation of variables
Measures of central tendency and variability
The basic concepts of probability
Stochastic independence, conditional probability
The probability distribution: the binomial and Gaussian distribution
The notions of sample and sample space
The sampling distributions: the distribution of the sample mean, of the difference between two sample averages and of the sample proportion
The concepts of punctual and interval estimation
The main tests of significance: the hypothesis testing on an average, on the difference between
averages, on a proportion
The concept of first and second species error and power of a statistical test
The Chi-square test
Correlation and simple linear regression
Introduction and basic elements of computer science
Calculator and peripherals
The software
IT and communication
Databases
Softwares: EXCEL and ACCESS
Expected Learning Outcomes
At the end of the course the student must have acquired the knowledge and full understanding of the topics deriving from the achievement of the educational objectives of each of the three teachings of the IC.
Knowledge and understanding: conduct an epidemiological investigation and use the appropriate statistical methods for data analysis. Knowing how to organize data through a spreadsheet or relational databases taking into account the requirements in terms of storage space, data transmission speed, security and privacy.
Ability to apply knowledge and understanding: apply the main models of observational and experimental studies in the epidemiological field. Ability to identify, quantify and evaluate the risk and protective factors for health and to use in the epidemiological survey the main epidemiological measures of frequency, risk and impact. Knowing how to solve and interpret exercises related to data analysis. Ability to concretely realize a database using current applications.
Making judgments: acquiring autonomy of judgment in conducting the analysis of data obtained from epidemiological studies by proposing appropriate solutions.
Communication skills: being able to describe the data and the results obtained from the statistical processing of epidemiological surveys through diagrams, tables, graphs. Knowing how to illustrate through the appropriate models the methodology used for data organization.
Learning skills: being able to study in depth themes of epidemiology, statistical analysis of data and organization of the same. Ability to learn independently how to use new IT tools.

Moduli

Course year 1
Code MS0938
Course EPIDEMIOLOGY
SSD MED/42
Campus ALESSANDRIA
Curriculum CORSO GENERICO
Credits 2
Course year 1
Code MS0936
Course COMPUTER SCIENCE
SSD INF/01
Campus ALESSANDRIA
Curriculum CORSO GENERICO
Credits 2
Course year 1
Code MS0937
Course MEDICAL STATISTICS
Lecturers Carlotta SACERDOTE
SSD MED/01
Campus ALESSANDRIA
Curriculum CORSO GENERICO
Credits 4
Last update:09-09-2026 00:14:31