
Course unit
PSYCHOMETRICS
PSL1000629, A.A. 2019/20
Information concerning the students who enrolled in A.Y. 2018/19
ECTS: details
Type 
ScientificDisciplinary Sector 
Credits allocated 
Basic courses 
MPSI/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 
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 Chisquare 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://statknowlab.unipd.it the student finds a free platform useful to improve the knowledge of statistics. Through an interactive system, StatKnowlab 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.

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

Spiegel M.R., Statistica. 975 problemi risolti. Milano: McGrawHill, 1994. Testo consigliato (non obbligatorio) per approfondimenti ed esercitazioni

Cristante F., Lis A., Sambin M., Problemi di statistica per psicologi. Padova: Upsel, 2014. Testo consigliato (non obbligatorio) per approfondimenti ed esercitazioni

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
Sustainable Development Goals (SDGs)

