First cycle
degree courses
Second cycle
degree courses
Single cycle
degree courses
School of Psychology
Course unit
PSP4068038, A.A. 2019/20

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

Information on the course unit
Degree course First cycle degree in
PS1842, Degree course structure A.Y. 2011/12, A.Y. 2019/20
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Number of ECTS credits allocated 6.0
Type of assessment Mark
Course unit English denomination PSYCHOMETRICS MOD. B
Department of reference Department of Developmental Psychology and Socialisation
Mandatory attendance No
Language of instruction Italian

Teacher in charge EGIDIO ROBUSTO M-PSI/03

Integrated course for this unit
Course unit code Course unit name Teacher in charge

ECTS: details
Type Scientific-Disciplinary Sector Credits allocated
Basic courses M-PSI/03 Psychometrics 6.0

Course unit organization
Period Second semester
Year 2nd Year
Teaching method distance e-learning

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

Start of activities 02/03/2020
End of activities 12/06/2020
Show course schedule 2019/20 Reg.2011 course timetable

Examination board
Examination board not defined


Common characteristics of the Integrated Course unit

Prerequisites: Equations and inequalities of the first and second degree; equation of line, of the parabola and of the circle in the plan, trigonometry: key relationships and functions; properties of powers and logarithms; elements of set theory, the concept of relation, function and properties; knowledge of elementary functions; basic geometry concepts.
Target skills and knowledge: This course covers statistical concepts and methods that can be applied in psychological research. The course is intended to provide a conceptual understanding of basic statistical procedures for exploring and understanding data in applied research. It also helps students develop the computational skills needed to carry out statistical procedures in practical settings.
Examination methods: The exam is written. The total duration of about 3 hours. The knowledge and skills of the contents of the two modules are investigated with two separate exams. The two texts are given at the beginning of the exam. The final grade is the average of the two grades (provided that both have a score greater than 18).
Assessment criteria: The evaluation of the performance of the student will be based on the comprehension of the statistical methodologies and the ability to apply them autonomously in a research context.

Specific characteristics of the Module

Course unit contents: -Principles of inferential statistics
-Some examples of inferential statistics methods
-Testing differences between means for one sample, two independent samples and two samples not independent
-Testing for association between categorical variables and contingency tables: the Pearson Chi-square test
-Analysis of the relationship between quantitative variables: regression and correlation analysis
Planned learning activities and teaching methods: Distance learning and exercises
Additional notes about suggested reading: useful to improve the knowledge of statistics. Through an interactive system, Stat-Knowlab tests the level reached by the student and proposes increasingly challenging exercises.
Recommended texts (NOT mandatory) for further insights and exercises:
- Cristante F., Lis A., Sambin M. (2014). "Problemi di statistica per psicologi". Upsel Domeneghini Editore, Padova.
- Ercolani A., Areni L., Leone L. (2002), Statistica per la psicologia: Fondamenti di psicometria e statistica descrittiva (Vol. I), Statistica inferenziale e analisi dei dati (Vol. II). Il Mulino, Bologna.
- Spiegel M.R. (1994). "Statistica. 975 problemi risolti". McGraw-Hill, Milano.
Textbooks (and optional supplementary readings)
  • Cristante F., Lis A., Sambin M., Statistica per psicologi. Firenze: Giunti, 2001. Par.: I.5, III.5, III.6, Cap. V Cerca nel catalogo

Innovative teaching methods: Teaching and learning strategies
  • Problem based learning
  • Case study
  • Interactive lecturing
  • Working in group
  • Problem solving
  • Loading of files and pages (web pages, Moodle, ...)

Innovative teaching methods: Software or applications used
  • Moodle (files, quizzes, workshops, ...)
  • One Note (digital ink)
  • Latex
  • R

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