First cycle
degree courses
Second cycle
degree courses
Single cycle
degree courses
School of Psychology
Course unit
PSP5070177, A.A. 2019/20

Information concerning the students who enrolled in A.Y. 2017/18

Information on the course unit
Degree course First cycle degree in
PS2192, Degree course structure A.Y. 2015/16, A.Y. 2019/20
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Number of ECTS credits allocated 6.0
Type of assessment Mark
Department of reference Department of General Psychology
E-Learning website
Mandatory attendance No
Language of instruction English
Single Course unit The Course unit CANNOT be attended under the option Single Course unit attendance
Optional Course unit The Course unit is available ONLY for students enrolled in PSYCHOLOGICAL SCIENCE

Teacher in charge GIOVANNI ZANZOTTO MAT/07

ECTS: details
Type Scientific-Disciplinary Sector Credits allocated
Educational activities in elective or integrative disciplines MAT/07 Mathematical Physics 6.0

Course unit organization
Period First semester
Year 3rd Year
Teaching method frontal

Type of hours Credits Teaching
Hours of
Individual study
Lecture 6.0 42 108.0 No turn

Start of activities 01/10/2019
End of activities 18/01/2020
Show course schedule 2019/20 Reg.2015 course timetable

Examination board
Board From To Members of the board
3 2019 01/10/2019 30/09/2020 ZANZOTTO GIOVANNI (Presidente)
CIATTI PAOLO (Membro Effettivo)
SPOTO ANDREA (Membro Effettivo)

Prerequisites: The mathematical knowledge necessary for the admission to the undergraduate course in Psychological Science is assumed.
Target skills and knowledge: The probability that a woman of age 40 has breast cancer is about 1 per cent. If she has breast cancer, the probability that she tests positive on a screening mammogram is 90 percent. If she does not have breast cancer, the probability that she nevertheless tests positive is 9 percent. What are the chances that a woman who tests positive actually has breast cancer? This class presents some basic techniques for the analysis of the uncertainty inherent in statistical information, with the goal of providing a correct evaluation and communication of risk. Basic notions of elementary probability theory and of Bayesian probability are introduced and discussed, and their application is illustrated in problems connected with the medical and psychological practice.
Examination methods: Written final exam with open questions or quizzes (4-6 exercises; duration: 70-90 minutes). The written exam verifies that the expected learning outcomes are actually acquired by the students through applicative questions, possibly including brief theoretical questions regarding the material presented in class.
The students will also make an oral presentation of a selected topic during class (topics chosen and researched by the students, under guidance of the instructor, working in groups of 3-4 people). Attendance to other students' presentations is considered part of the required coursework.
Assessment criteria: Grading is based on the results of the final written test, and on the performance in the oral presentation (the presentation contributes about 20% to the final course grade).
Course unit contents: Uncertainty in statistical information. Problems related to the evaluation of risk and communication of risk. Real-world examples. Bayesian inferences through the use of probabilities and by means of natural frequencies. Suitability of the latter for a more intuitive and direct insight in both risk estimation and in a transparent representation of risk. Examples focussing on the correct judgement of the probabilistic predictive value of medical diagnostic tests, and aiming at avoiding misleading risk information. Evaluation of the effect of interventions: Relative risk and Absolute Risk, and Relative and Absolute Risk Reduction (or Increase); Number Needed to Treat or to Harm [ARR, RR, RRR, NNT, NNH].
Planned learning activities and teaching methods: Class lectures, with presentation of the main points mentioned above. Some theory and many examples. Recitations and exercises to complement the theoretical parts, also directly involving students in both individual and group work. The main focus is on real-world applications of the topics treated during the coursework.
Additional notes about suggested reading: The textbook is required reading, and further material is made available through moodle during class. See also the extra reading material indicated in the references below.
Textbooks (and optional supplementary readings)
  • MAIN TEXTBOOK ---- Gerd Gigerenzer, Calculated Risk. New York: Simon & Schuster, 2002. Cerca nel catalogo
  • Auxiliary reading material ---- Gerd Gigerenzer et al., Helping Doctors and Patients Make Sense of Health Statistics. --: Association for Psychological Science, 2008.
  • Auxiliary reading material ---- Stephanie Kurzenh√§user, Natural frequencies in medical risk communication: improving statistical thinking in physicians and patients. Dissertation: FU Berlin, 2003.
  • Auxiliary reading material ---- M. R. Spiegel, Theory & Problems Of Probability & Statistics. New York: Schaum Mc Graw Hill, 1998.

Innovative teaching methods: Teaching and learning strategies
  • Lecturing
  • Interactive lecturing
  • Working in group
  • Questioning
  • Problem solving
  • Loading of files and pages (web pages, Moodle, ...)

Innovative teaching methods: Software or applications used
  • Moodle (files, quizzes, workshops, ...)

Sustainable Development Goals (SDGs)
Good Health and Well-Being Gender Equality Decent Work and Economic Growth Reduced Inequalities Responsible Consumption and Production Peace, Justice and Strong Institutions