First cycle
degree courses
Second cycle
degree courses
Single cycle
degree courses
School of Psychology
APPLIED COGNITIVE PSYCHOLOGY
Course unit
STATISTICAL METHODS FOR CLINICAL RESEARCH
PSO2043915, A.A. 2015/16

Information concerning the students who enrolled in A.Y. 2015/16

Information on the course unit
Degree course Second cycle degree in
APPLIED COGNITIVE PSYCHOLOGY
PS1978, Degree course structure A.Y. 2014/15, A.Y. 2015/16
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Number of ECTS credits allocated 6.0
Type of assessment Mark
Course unit English denomination STATISTICAL METHODS FOR CLINICAL RESEARCH
Department of reference Department of General Psychology
E-Learning website https://elearning.unipd.it/scuolapsicologia/course/view.php?idnumber=2015-PS1978-000ZZ-2015-PSO2043915-N0
Mandatory attendance No
Language of instruction Italian
Branch PADOVA
Single Course unit The Course unit can be attended under the option Single Course unit attendance
Optional Course unit The Course unit can be chosen as Optional Course unit

Lecturers
Teacher in charge GIOVANNA CAPIZZI SECS-S/01

Mutuating
Course unit code Course unit name Teacher in charge Degree course code
PSO2043915 STATISTICAL METHODS FOR CLINICAL RESEARCH GIOVANNA CAPIZZI PS1091

ECTS: details
Type Scientific-Disciplinary Sector Credits allocated
Educational activities in elective or integrative disciplines SECS-S/01 Statistics 6.0

Course unit organization
Period First semester
Year 1st Year
Teaching method frontal

Type of hours Credits Teaching
hours
Hours of
Individual study
Shifts
Lecture 6.0 42 108.0 No turn

Calendar
Start of activities 12/10/2015
End of activities 15/01/2016
Show course schedule 2019/20 Reg.2017 course timetable

Examination board
Board From To Members of the board
2 2017-1 01/10/2017 30/09/2018 CAPIZZI GIOVANNA (Presidente)
PASTORE MASSIMILIANO (Membro Effettivo)
TARANTINO VINCENZA (Membro Effettivo)
1 2017 01/10/2016 30/09/2017 CAPIZZI GIOVANNA (Presidente)
PASTORE MASSIMILIANO (Membro Effettivo)
TARANTINO VINCENZA (Membro Effettivo)

Syllabus
Prerequisites: Students need to have elementary knowledge of probability and basic statistics.
Target skills and knowledge: Introduction of the main statistical tools, univariate and multivariate, for biomedical applications. Students will develop skills to analyze, using a statistical software, the relationship between a specific bio-medical/psychological status and several predictors.
Examination methods: Written examination. Multiple choice questions concerning the statistical analysis of real data. Reports and analysis are performed in the lab using the R software.
Assessment criteria: The evaluation of the preparation of students will be based on the understanding of the handled topics, the acquisition of concepts and skills to apply them.
Course unit contents: Univariate and multivariate explorative statistical analysis of collected data. Statistical tools for testing association and
dependence among categorial and continuous experimental data in the biomedical framework: model free techniques for multiway contingency tables. Generalized Linear Models (linear and logistic multiple regression). ANOVA for independent and repeated measures. Introduction to non-parametric statistics. Tree-based procedures.
Planned learning activities and teaching methods: Lectures.

Labs are the core of the course. Case studies are analyzed using the R language. Practical problems are discussed doing an accurate exploratory data analysis and fitting suitable univariate and multivariate statistical models.
Additional notes about suggested reading: Slides of the lectures and written comments to the case studies, discussed during labs, will be available on the website.
Textbooks (and optional supplementary readings)
  • Triola M. M., Triola M. F., “Statistica per le discipline biosanitarie“. --: Pearson Education It, 2009. Cap. 1-8, 10, 12 Cerca nel catalogo
  • Fox J., Applied regression analysis, linear models, and related methods. --: Sage, 1997. Cap. 5-15 Cerca nel catalogo