First cycle
degree courses
Second cycle
degree courses
Single cycle
degree courses
School of Medicine
NURSING AND MIDWIFERY SCIENCES
Course unit
LABORATORY OF STATISTICS
MEO2043337, A.A. 2017/18

Information concerning the students who enrolled in A.Y. 2016/17

Information on the course unit
Degree course Second cycle degree in
NURSING AND MIDWIFERY SCIENCES
ME1867, Degree course structure A.Y. 2015/16, A.Y. 2017/18
N0
bring this page
with you
Number of ECTS credits allocated 3.0
Type of assessment Evaluation
Course unit English denomination LABORATORY OF STATISTICS
Website of the academic structure https://www.medicinamolecolare.unipd.it
Department of reference Department of Molecular Medicine
Mandatory attendance
Language of instruction English
Branch PADOVA
Single Course unit The Course unit CANNOT be attended under the option Single Course unit attendance
Optional Course unit The Course unit is available ONLY for students enrolled in NURSING AND MIDWIFERY SCIENCES

Lecturers
Teacher in charge DARIO GREGORI MED/01

ECTS: details
Type Scientific-Disciplinary Sector Credits allocated
Other MED/01 Medical Statistics 3.0

Mode of delivery (when and how)
Period Second semester
Year 2nd Year
Teaching method frontal

Organisation of didactics
Type of hours Credits Hours of
teaching
Hours of
Individual study
Shifts
Laboratory 3.0 30 45.0 No turn

Calendar
Start of activities 26/02/2018
End of activities 01/06/2018

Examination board
Board From To Members of the board
4 Commissione 2016/17 01/10/2016 30/04/2018 GREGORI DARIO (Presidente)
ZANOTTI RENZO (Membro Effettivo)

Syllabus
Prerequisites: Basic knowledge of medical statistics, as in the undergraduate courses (theory of estimation and tests, descriptive statistics) and regression methods (linear and logistic regression, Cox model).
Basic use of PC (Office and internet).
Target skills and knowledge: The student shall develop the ability to conduct the analysis of a real-world case study, by selecting appropriate techniques and by implementing them using the PC. The software used i the R System.
Examination methods: Real-time analysis of a data-set, using R.
Assessment criteria: Capability and independence in analyzing health data.
Course unit contents: Introduction to R
Import/export of data
Exploratory analysis and plots in R
RMS libraries
Planned learning activities and teaching methods: Front classes and interactive individual work at the PC
Additional notes about suggested reading: Material provided in class.
Textbooks (and optional supplementary readings)