DATA PROCESSING
cod. 1007355

Academic year 2021/22
1° year of course - First semester
Professor
Matteo GOLDONI
Academic discipline
Statistica medica (MED/01)
Field
Inglese scientifico e abilità linguistiche, informatiche e relazionali, pedagogia medica, tecnologie avanzate e a distanza di informazione e comunicazione
Type of training activity
Characterising
30 hours
of face-to-face activities
3 credits
hub: PARMA
course unit
in ITALIAN

Integrated course unit module: PROPAEDEUTIC SCIENCES I

Learning objectives

At the end of the course, students should be able: - to create and manage a clinical database with several variables with excel, starting from real cases (i.e. clinical records or questionnaires); -to import this database on other statistical software and to perform tests of inferential and descriptive statistics; - to perform simple models of multivariate statistics.

Prerequisites

No

Course unit content

The course is strictly related to medical statistics, which will be done simultaneously.
PROGRAM
Data in biomedical field. Software for data processing. Database definition. Excel: principles and operations. To build a database and in Excel and to export it into a specific statistical software. Numerical, text, and grouping variables in the database. Operations among variables. The use of functions in Excel. Graphs in Excel. The use of freeware statistical software and SPSS. More than two groups: analysis of variance (one-way ANOVA). From univariate to multivariate statistics: data processing with several variables. Multiple regression. Logistic regression. Two-way ANOVA. Processing of survival data: Kaplan-Meier curves and Cox regression. ROC curves and the diagnosis through a pattern of variables.
The management of an electronic database.

Full programme

Contents include the extended program.

Bibliography

Classroom slides (uploaded during the course) and all the material on Elly are the reference point for the exam. Some further reference books: SA Glantz -
Statistica per discipline biomediche - McGraw-Hill. All the books about Excel, ACCESS and SPSS.

Teaching methods

This course is parallel to that of medical statistics. During the frontal lessons, the arguments of the course will be explained and commented. However, a part of the teaching hours will be used to comment and discuss with the students the on-line material, which will comprehend practical examples, explanations about the use of freeware software/SPSS/Excel, and comments about recent scientific articles. Therefore, each theoretical argument with mathematical formulae will be explained by using simple and practical examples, so that students may focus on basic concepts more than on the formulae. Several technical terms will be used both in Italian and in English, so that the student can read on his own the international scientific literature, particularly in the field of clinical medicine. The use of computer during the lessons is encouraged.
Lectures will be held on-site in compliance with safety standards, provided that further instructions on the ongoing health emergency are not implemented. Supporting material will be available on the specific, student-reserved platform (Elly) and will include slide presentations, audio-video aids or video-recording of the lectures.

Assessment methods and criteria

The evaluation of the students will be formative, as the aptitude test in medical statistics and data processing will be done in more than one step during the course. The tests will be at least two and will be performed by students on-line on Elly platform at fixed dates and hours or in a written form (multiple response test). If a student prefers a summative evaluation and/or does not pass the formative evaluation, he/she can do a final overall test on all the arguments treated during the course (multiple response test).
The exam will be done in presence or on-line (elly platform), depending on the pandemic course.

Other information

- - -

2030 agenda goals for sustainable development

- - -

Contacts

Toll-free number

800 904 084

Student registry office

E. [segreteria.medicina@unipr.it] 
T. +39 0521 033700

Quality assurance office

Education manager

Giovanna Caselli
T. +39 0521 033851
Office E. didattica.dimec@unipr.it] 
Manager E. [giovanna.caselli@unipr.it] 

President of the degree course

[Prof.] [Marcello Giuseppe] [Maggio]
E. [marcellogiuseppe.maggio@unipr.it]

Faculty advisor

[Prof.] [Stefano] [Guizzardi]
E. [stefano.guizzardi@unipr.it] 

[Prof.] [Aderville] [Cabassi]
E. [aderville.cabassi@unipr.it] 

Career guidance delegate

[Prof.] [Stefano] [Guizzardi]
E. [stefano.guizzardi@unipr.it] 

[Prof.] [Aderville] [Cabassi]
E. [aderville.cabassi@unipr.it] 

Tutor Professors

[titolo] [nome] [cognome]
E. [email @unipr] (modificare link a email)

Erasmus delegate

[Prof.ssa] [Alessandra] [Dei Cas]
E. [alessandra.deicas@unipr.it] 
[Prof.ssa] [Mara] [Bonelli]
E. [mara.bonelli@unipr.it] 

[Prof.ssa] [Valentina] [Cannone]
E. [valentina.cannone@unipr.it] 

[Prof.] [Andrea] [Ticinesi]
E. [andrea.ticinesi@unipr.it] 

[Prof.] [Roberto] [Sala]
E. [roberto.sala@unipr.it] 

Quality assurance manager

[Prof.] [Paolo] [Del Rio]
E. [paolo.delrio@unipr.it] 

Tutor students

[titolo] [nome] [cognome]
E. [email @unipr] (modificare link a email)