First cycle
degree courses
Second cycle
degree courses
Single cycle
degree courses
School of Psychology
CLINICAL DEVELOPMENTAL PSYCHOLOGY
Course unit
STATISTICAL METHODS IN DEVELOPMENTAL PSYCHOLOGY
PSP6074640, A.A. 2018/19

Information concerning the students who enrolled in A.Y. 2018/19

Information on the course unit
Degree course Second cycle degree in
CLINICAL DEVELOPMENTAL PSYCHOLOGY
PS2292, Degree course structure A.Y. 2016/17, A.Y. 2018/19
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Number of ECTS credits allocated 3.0
Type of assessment Evaluation
Course unit English denomination STATISTICAL METHODS IN DEVELOPMENTAL PSYCHOLOGY
Department of reference Department of Developmental Psychology and Socialisation
E-Learning website https://elearning.unipd.it/scuolapsicologia/course/view.php?idnumber=2018-PS2292-000ZZ-2018-PSP6074640-N0
Mandatory attendance No
Language of instruction Italian
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 CLINICAL DEVELOPMENTAL PSYCHOLOGY

Lecturers
Teacher in charge GIANMARCO ALTOE' M-PSI/03

ECTS: details
Type Scientific-Disciplinary Sector Credits allocated
Other -- -- 3.0

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

Type of hours Credits Teaching
hours
Hours of
Individual study
Shifts
Lecture 3.0 21 54.0 No turn

Calendar
Start of activities 25/02/2019
End of activities 14/06/2019
Show course schedule 2019/20 Reg.2016 course timetable

Examination board
Board From To Members of the board
2 2018 01/10/2018 30/09/2019 ALTOE' GIANMARCO (Presidente)
CALCAGNI' ANTONIO (Membro Effettivo)
PASTORE MASSIMILIANO (Membro Effettivo)

Syllabus
Prerequisites: A basic knowledge of Psychometrics Statistics is required. Attend the course Data analysis for behavioral science is preferable.
Target skills and knowledge: The aim of this short course is to offer students relevant insight in a few statistical methods which are commonly used in Developmental Psychology, enable students to use the statistical software R, and to help and advice them for data analysis realizations (data analysis and discussions of results)
Examination methods: The exam will take place during the last lesson of the course or on a date established ad hoc by the teacher. It will focus on the contents discussed during the course, with particular reference to the application and operational components learned. The modalities of the examination will therefore be in line with the experiential techniques already used during the lessons, and aim at verifying the extent to which students have acquired the pragmatic components of the instruments, techniques and / or models presented during classroom activities.
In particular, presentation and discussion of a complete data analysis report (which will involve students selecting a case-study, performing data-analyses, and writing a final report showing findings) will be requested.
Assessment criteria: Since the laboratory consists of a professionalizing and experiential teaching formula, the evaluation criteria of students learning will focus specifically on these aspects. Particular emphasis will be placed on the empirical, clinical and operational implications of the tools, as well as on the methods and techniques presented during the laboratory. Further elements contributing to the definition of the final evaluation will be students active participation during the lessons, the activities carried out autonomously for the application of the contents presented, and the participatory and shared presence in the working groups.
Course unit contents: The course of Statistical Methods In Developmental Psychology is part of the set of laboratories offered within the Second Cycle Degree in Clinical Developmental Psychology. The laboratory activity will be provided in small groups (maximum 20 students) in the presence of the professor. Experiential and professionalizing learning techniques will be used
In particular, the following topics will be covered:
- Overview of the basic concepts in Statistics (3 h)
- Introduction to R (3 h)
- Analysis of real case studies (12 h)
Students will learn analysing and discussing real case studies in the domain of Developmental psychology. Case studies will be chosen by students under the supervision of the lecturer. Students will also select and examine in depth the most appropriate data analysis techniques to the chosen case studies.
- Presentation and discussion of the final findings (3 h)

Note: All the classes will be held in a computer room. In addition, international students can be supervised in English.
Planned learning activities and teaching methods: Classroom activities require the regular attendance of students, who will be divided into small groups to facilitate their learning process in terms of the professional and experiential basis of the contents that define the laboratory activities themselves. In this perspective, students participation in at least 70% of the lessons is recommended to allow for an in-depth understanding of the learning contents. Group work in the classroom is an integral part of the teaching method of the laboratory and is one of the learning activities, in addition to the assessment of students’individual contribution. Students who, for exceptional reasons, are unable to attend are advised to contact the professor in a timely manner to arrange for alternative activities.
In particular, the course will start with a brief introduction with standard lessons. Next, interactive classes with discussions during lecturing time and group assignments will be organized.
Additional notes about suggested reading: Slides, readings, and data will be available on Moodle
Textbooks (and optional supplementary readings)

Innovative teaching methods: Teaching and learning strategies
  • Laboratory
  • Case study
  • Working in group
  • Loading of files and pages (web pages, Moodle, ...)
  • Students peer review

Innovative teaching methods: Software or applications used
  • Moodle (files, quizzes, workshops, ...)
  • R: a free software environment for statistical computing and graphics

Sustainable Development Goals (SDGs)
Quality Education