| 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
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 |
 bring this page with you |
|---|---|---|
| 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 |
| 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) |
| 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) |
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