First cycle
degree courses
Second cycle
degree courses
Single cycle
degree courses
School of Psychology
SOCIAL, WORK AND COMMUNICATION PSYCHOLOGY
Course unit
MULTIVARIATE CORRELATION TECHNIQUES IN PSYCHOSOCIAL RESEARCH
PSN1032473, A.A. 2019/20

Information concerning the students who enrolled in A.Y. 2019/20

Information on the course unit
Degree course Second cycle degree in
SOCIAL, WORK AND COMMUNICATION PSYCHOLOGY
PS1087, Degree course structure A.Y. 2017/18, A.Y. 2019/20
N0
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Number of ECTS credits allocated 6.0
Type of assessment Mark
Course unit English denomination MULTIVARIATE CORRELATION TECHNIQUES IN PSYCHOSOCIAL RESEARCH
Department of reference Department of Philosophy, Sociology, Education and Applied Psychology
E-Learning website https://elearning.unipd.it/scuolapsicologia/course/view.php?idnumber=2019-PS1087-000ZZ-2019-PSN1032473-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 ANNA MARIA MANGANELLI M-PSI/05

ECTS: details
Type Scientific-Disciplinary Sector Credits allocated
Core courses M-PSI/05 Social Psychology 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 07/10/2019
End of activities 18/01/2020
Show course schedule 2019/20 Reg.2017 course timetable

Examination board
Board From To Members of the board
9 2019/20 01/10/2019 30/11/2020 MANGANELLI ANNA MARIA (Presidente)
BOBBIO ANDREA (Membro Effettivo)
CANOVA LUIGINA (Membro Effettivo)
8 2018/19 01/10/2018 30/11/2019 MANGANELLI ANNA MARIA (Presidente)
BOBBIO ANDREA (Membro Effettivo)
CANOVA LUIGINA (Membro Effettivo)

Syllabus
Prerequisites: Knowledges of Psychometric, Methodology of psychosocial research (or equivalent) and Social Psychology are necessary.
Target skills and knowledge: This course aims to introduce the students to basic knowledge for applying major techniques of multivariate analysis in Social Psychology. The expected knowledge and skills are as follows:
- know the logic and the foundations of multivariate analysis;
- know and apply the basic calculation procedures for the analysis of multiple regressions;
- know the theoretical and mathematical foundations of factor analysis;
- be able to read and interpret output regarding multiple regression analysis and factor analysis obtained with a statistical package (SPSS).
Examination methods: The exam is written with multiple-choice and open questions, and exercises. Oral examination is not allowed.
Assessment criteria: Students' performance on the exam will be evaluated in terms of the understanding of the topics and in terms of the acquisition of concepts, technical-statistic language and methods of data analysis proposed during the course; will be considered also the capacity to apply methods autonomously and consciously.
Course unit contents: - Correlational research in Social psychology and the logic of multivariate analysis.
- Partial and multiple correlation.
- Multiple regression.
- Mediation and moderation: definitions and analysis.
- Factor analysis: principal component and factor analysis models.
- Applications of factor analysis in the development of measurement instruments for research in social psychology.
Planned learning activities and teaching methods: The lessons, typically frontal, will concern the subjects above described. The student will deepen the topics by using the text books, the didactic materials and other readings suggested during the lessons. Some practical experiences are dedicated to learning of some calculus techniques, to description and discussion of research results.
Additional notes about suggested reading: All class materials will be made available on-line (on School of Psychology Moodle platform).
Textbooks (and optional supplementary readings)
  • Gallucci, M. Leone, L. e Berlingeri, M., Modelli statistici per le scienze sociali (seconda edizione). Milano: Pearson, 2017. Cap 1, 2, 3, 4 (solo i par. 4.1 e 4.2) 5 (no i par. 5.6 e 5.7), 6 (solo par. 6.5), 7 (solo par. 7.1, 7.2, 7.3), 13 (no i par. 13.4.3, 13.4.4, 13.4.5) Cerca nel catalogo
  • Barbaranelli C., Analisi dei dati con SPSS. Le analisi multivariate. Milano: Led, 2006. Capitoli 1 e 2. Cerca nel catalogo

Innovative teaching methods: Teaching and learning strategies
  • Lecturing
  • Questioning
  • Active quizzes for Concept Verification Tests and class discussions
  • Loading of files and pages (web pages, Moodle, ...)

Innovative teaching methods: Software or applications used
  • Moodle (files, quizzes, workshops, ...)