93214 - Psychometric and Data Analysis Techniques

Course Unit Page


This teaching activity contributes to the achievement of the Sustainable Development Goals of the UN 2030 Agenda.

Good health and well-being

Academic Year 2021/2022

Learning outcomes

At the end of the training activity, the student is able to: - carry out a project for the construction, validation and normalization of the neuropsychological tests; - conduct a statistical analysis appropriate to the experimental design; - interpret the results of the statistical analysis.

Course contents

The course takes place in the first semester (from October to December 2020) for the first year students. For all the students, lessons are held online via the Teams platform. The training activity aims to offer theoretical and methodological tools for the application of advanced statistical techniques for the construction and standardization of tests and for the analysis of data used in research in neuropsychology and neuroscience.

Exercises on statistical analyzes will be presented in the laboratory.

Part I Statistical tests and methodological basis for the construction, validation and standardization of neuropsychological tests

Factor analysis

Standard values and ranges
- confidence and tolerance intervals
- Normal and Student's intervals
- Non-parametric intervals
Classification threshold
- Sensitivity and Specificity
- ROC Curves

Part II Inferential tests for multivariate designs

General Linear Model
Binomial Logistic regression


Mandatory texts and materials that are propedeutic to the course:

  • Statistics in Psychology with SPSS (7e) By DennisHowitt, DuncanCramer Pearson Edition 2017
  • Teaching material provided by the teacher and available on the University platform at iol.unibo.it
  • Examples of Exam tests available online at iol.unibo.it

Recommended in-depth readings:

  • Scientific papers given by the lecturer

Teaching methods

Frontal lectures, seminars and group work

Given the numerous examples of in-depth studies carried out in the classroom it is advisable to actively attend the lessons.

In the case of special needs, the lecturer can be contacted in order to jointly activate with the University Service for students with disabilities and Specific Learning Disorders the appropriate support methods.

Because of the type of activity and method of the course, the participation at this teaching activity requires the participation at the online course 1 and  2 about security in study places, [https://elearning-sicurezza.unibo.it/]  .

Assessment methods

Discussion on a paper prepared by the student at the end of the course.

The student has to prepare a paper concerning two topics referring to the program (one selected from the first part, the other from the second).

For each topic, the paper consists of a theoretical part concerning the description of the selected statistical model, and of a critical application of the model. For the critical application the student has two alternatives. The first alternative consists of a critical application of the model to a specific data collected previously during lectures; The second choice consists of a critical revision on a scientific manuscript concerning the selected statistical model. The maximum length is 6000 words.

The paper has to be sent together with the scientific manuscript to the docent by e-mail one week before the official date of the exam. During the exam the paper will be discussed orally.

The paper is evaluated on the basis of the criteria: 1. clarity (maximum score 10 points: from 0 to 3 elaborated unclear; from 4 to 6 elaborated sufficiently clear; from 7 to 9 elaborated fairly clear; 10 elaborate clear) ka clarity is evaluated as consistency of the arguments, presence of logical connections between the parts and expository fluidity; completeness (maximum score 20: 0 if processed out of topic; from 1 to 5 for completeness in the theoretical part, from 1 to 5 for completeness in the application part of each of the two themes; 1 is assigned for lack of completeness, that is lacking the most of the information; 2 missing a lot of information; 3 there is the essential information; 4 there is all the information; 5 there are additional personal reflections). The paper will be evaluated according to a 30 points score and this score will be considered together with the oral presentation (the total score will represent the mean of the two scores). Laude is awarded for excellent written and oral assignments. The minimum score for the paper is 18. If the paper is less than 18, the correction of the errors and the new presentation of the paper are required. The teacher will communicate the errors to the student and will agree with him for a new exam date.

The oral exam will cover the whole program. You will be asked to answer theoretical questions regarding the course topics to see if the course objectives have been achieved.

The minimum score is 18. in the case of a score below 18, the student is required to revise the paper and present it again according to the suggestion of the docent. The docent and the student will schedule the new oral presentation.Due to the current situation due to the Covid-19 emergency, the oral exam will be carried out on the Teams platform. If there is the possibility of taking the exam in person, this opportunity will be indicated in the teacher's stio on the Notices page. Students regularly enrolled in the exam session will receive an invitation to participate in the exam automatically on the day of the exam.

In the case of special needs, the lecturer can be contacted in order to jointly activate with the University Service for students with disabilities and Specific Learning Disorders the appropriate support methods.

To take the exam it is necessary to register through the electronic bulletin board, in compliance with the established deadlines. Those who are unable to register for technical problems by the scheduled date, are required to promptly (and in any case before the official closing of the registration lists) communicate the problem to the didactic secretariat. The teacher will be able to admit them to take the test.

Teaching tools

Frontal lectures are supported by different materials:

- books and electronic book

- scientific articles

Teaching material provided by the teacher and available on the University platform at iol.unibo.it

Office hours

See the website of Mariagrazia Benassi