First cycle
degree courses
Second cycle
degree courses
Single cycle
degree courses
School of Psychology
SOCIAL AND WORK PSYCHOLOGY
Course unit
PSYCHOMETRICS
PSL1000629, 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
SOCIAL AND WORK PSYCHOLOGY
PS1085, Degree course structure A.Y. 2017/18, A.Y. 2019/20
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Number of ECTS credits allocated 12.0
Type of assessment Mark
Course unit English denomination PSYCHOMETRICS
Department of reference Department of Philosophy, Sociology, Education and Applied Psychology
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 EGIDIO ROBUSTO M-PSI/03
Other lecturers LUCA STEFANUTTI M-PSI/03

ECTS: details
Type Scientific-Disciplinary Sector Credits allocated
Basic courses M-PSI/03 Psychometrics 12.0

Course unit organization
Period First semester
Year 2nd Year
Teaching method frontal

Type of hours Credits Teaching
hours
Hours of
Individual study
Shifts
Lecture 12.0 84 216.0 No turn

Calendar
Start of activities 01/10/2019
End of activities 18/01/2020
Show course schedule 2019/20 Reg.2017 course timetable

Syllabus
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: Written exam of three hours long with open or closed questions. The student can use books, notes, tables or statistical forms.
Assessment criteria: The evaluation covers both the knowledge of theoretical topics, and their practical application. To be considered sufficient, the student must answer correctly to most of the proposed exercises.
Course unit contents: First part of the course (8 CFU) - Prof. Egidio Robusto
1) Prerequisites review
2) Outline of measurement theory and classification of measurement scales
3) The main descriptive statistics and their measurement significance
4) Random variables and probability laws, discrete and continuous
5) Principles of inferential statistics
6) Some examples of inferential statistics methods

Second part of the course (4 CFU) - Prof. Luca Stefanutti
1) Testing differences between means for one sample, two independent samples and two samples not independent
2) Testing for association between categorical variables and contingency tables: the Pearson Chi-square test
3) Analysis of the relationship between quantitative variables: regression and correlation analysis
Planned learning activities and teaching methods: Besides the lectures, exercises on concrete analysis cases will be proposed in which the students, alone or in a group, will have the opportunity to test the concepts learned.
Additional notes about suggested reading: On the course's Moodle page will be made available to students the slides of the lectures, some exercises accompanied by solutions, and any material used in class.
Moreover, at the internet address http://stat-knowlab.unipd.it the student finds a free platform 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.
It is stressed that the availability of such material in no way can be considered a substitute of the lectures frequency, which remains the most effective way to approach the discipline.
Textbooks (and optional supplementary readings)
  • Cristante F., Lis A., Sambin M., Fondamenti teorici dei metodi statistici in psicologia. Padova: Upsel, 2014. Cerca nel catalogo
  • Cristante F., Lis A., Sambin M., Statistica per psicologi. Firenze: Giunti, 2001. Prima parte del corso: Par.: da I.1 a I.4, da II.1 a II.3, da III.1 a III.4 - Seconda parte del corso: Par.: I.5, III.6; Cap.: V Cerca nel catalogo
  • Spiegel M.R., Statistica. 975 problemi risolti. Milano: McGraw-Hill, 1994. Testo consigliato (non obbligatorio) per approfondimenti ed esercitazioni Cerca nel catalogo
  • Cristante F., Lis A., Sambin M., Problemi di statistica per psicologi. Padova: Upsel, 2014. Testo consigliato (non obbligatorio) per approfondimenti ed esercitazioni 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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