Course Syllabus
Aims
The laboratory aims to introduce the student to the investigation of questions of psychological importance through the methods and tools of data science.
Contents
Human behavior is extremely complex, as it is affected by many factors. Many psychological experiments measure 2-7 variables in cross-sectional studies with small datasets.
The use of large datasets, with many variables and/or longitudinal designs, is sporadic. However, the research conducted so far with “Big Psychological Data” demonstrates that the use of machine learning methods, such as clustering and deep learning, can be applied to solve complex psychological problems.
We will address several problems of applied psychological interest, with case studies.Detailed program
We will cover psychological aspects related to consumer and costumer behavior , with particular attention to naturally occurring datasets (I.e., digital traces of behavior and cognition).
Examples of psychological addressed in the laboratory are:
- determinants of pro-environmental consumption
- cognitive bias in purchasing behavior
Prerequisites
Basic knowledge of R (https://www.r-project.org) or other statistical software.
Teaching form
We will analyze several case studies:
- the research question;
- how it has been addressed and with which results;
- spaces for improvements.
Textbook and teaching resource
Slides and scientific papers will be made available on the e-learning page.
Semester
Second Semester
Assessment method
- Computerized written examination on the theoretical concepts (with open and closed questions)
and
- Final project, based on a work in small groups of up to 3 participants.