02225 - Psychometric Statistics

Course Unit Page

Academic Year 2018/2019

Learning outcomes

At the end of the course the student: a) know the statistical tests used in psychological research; b) is able to select properly the statistical procedure for different research hypothesis; c) is able to discuss the results obtained by the analysis

Course contents

The course will take place during the second semester (from February to May) at the Cesena Campus of the School of Psychology and Education (address: piazza A. Moro, 90).

Part I: Epistemological basis of Statistical inference

The concept of Probability: theoretical definitions

Probability properties

Probability distributions: Binomial, Normal, Chi square, t, F

Descriptive statistics: applications

Inferential statistics

· Basis of the statistical testing

· Null hypothesis, Significance, Power,

Effect size

PART II: The use of the inferential statistics

Parametric Tests

· Student t-test

· Analysis of variance

· Regression analysis

· Repeated measures analysis of variance

· General Linear Model

Non-parametric tests

· Contingency tables: Chi square test, Fisher exact test

· Sign test

· Rank tests


Howitt D and Cramer D (2014) Introduction to Statistics in Psychology Pearson Education INc.

Teaching methods

Frontal lectures and seminar of discussion, Group work

Assessment methods

The exam consists of a written test to check the achievement of the abilities described in the learning outcomes. The candidate is asked to study the topics related to the statistical testing logic, their procedures and their assumptions.

The written exam consists of 31 multiple choice questions  (time 50 minutes). The minimum score to pass the exam is 18. Every topic of the program could be object of the exam and will have the same weight in the evaluation process. The grade will be on a scale of 30.

The student is required to complete the online registration within the terms in order to be admitted to the exam. In the case of technical problems the student is required to contact the docent by e-mail. The docent will consider the request and decide about the admission.



Teaching tools

Frontal lectures are supported by different materials:

- books and electronic book

- scientific articles


Office hours

See the website of Mariagrazia Benassi