- Docente: Jacopo Lenzi
- Credits: 4
- SSD: MED/01
- Language: Italian
- Teaching Mode: Traditional lectures
- Campus: Bologna
- Corso: Single cycle degree programme (LMCU) in School of Dentistry (cod. 6738)
Learning outcomes
Al termine del corso lo studente possiede una preparazione che gli consenta di comprendere le basi metodologiche della Statistica medica, con particolare riguardo alle applicazioni in Odontoiatria e Protesi Dentaria. In particolare lo studente è in grado di: i) conoscere ed utilizzare le tecniche di statistica descrittiva ed inferenziale; ii) identificare le tecniche di analisi statistica più adeguate ai dati raccolti; iii) riconoscere l'organizzazione e le caratteristiche dei diversi tipi di studio epidemiologico sia osservazionale che sperimentale; iv) conoscere i criteri attraverso i quali si valuta l'affidabilità di una tecnica diagnostica; v) conoscere la metodologia di base per impostare una ricerca in Odontoiatria e Protesi Dentaria; vi) possedere le basi per l'interpretazione dei risultati di una ricerca in Odontoiatria e Protesi Dentaria; vii) riconoscere la qualità di un articolo scientifico; viii) coordinare le conoscenze specifiche con quelle delle discipline di base per riconoscere la capacità di un risultato scientifico di rispondere ai criteri della Evidence Based Dentistry.
Course contents
Observation units, variables, and measurement scales.
Statistical data collection and database setup.
Frequency distributions and graphical representations.
Measures of central tendency and variability.
Shape of a frequency distribution.
Relationship between two variables: contingency tables and correlation indices.
Introduction to probability: random variables and probability models.
Random sampling, estimator theory, and confidence intervals.
Statistical tests for comparing means, proportions, and distributions.
Linear and logistic regression models.
Introduction to Poisson and Cox regression models.
Measures of diagnostic accuracy.
Main types of epidemiological study design.
Measures of occurrence and association in epidemiology.
Readings/Bibliography
Pagano, M., & Gauvreau, K. (2003). Biostatistica (2nd Italian ed.). Naples: Idelson-Gnocchi. [Chapters 1–3, 6–21]
Bonita, R., Beaglehole, R., & Kjellström, T. (2006). Basic epidemiology (2nd ed.). Geneva: World Health Organization. [Chapters 1–3, 5, 8]. [Free download: https://apps.who.int/iris/bitstream/handle/10665/43541/9241547073_eng.pdf?sequence=1&isAllowed=y]
Teaching methods
Lectures and exam simulations.
Assessment methods
The final exam is a paper-based, multiple-choice test consisting of 20 questions (each with 4 choices, only one of which is correct), to be completed in 25 minutes. The test covers only the content of the Medical Statistics teaching unit.
The exam is passed with at least 10 correct answers. There are no penalties for wrong or blank answers. Students who fail the exam can retake it on the next available date (there is no restriction on consecutive attempts).
The use of calculators is not required. The use of formula sheets or any other supporting materials is not permitted. Non-native Italian speakers are encouraged to use a bilingual dictionary.
Grades will be sent by email to each student's institutional address (@studio.unibo.it). The student has three days to reject the grade by replying to the professor's message. After that, the grade will be considered accepted.
Reviewing the exam with the professor is possible, upon request, only in case of a failing grade. Details about the test questions or the student's incorrect answers will not be shared by email.
Students with specific learning disorders (SLD) or those with temporary or permanent disabilities are advised to contact the relevant office in advance (https://site.unibo.it/studenti-con-disabilita-e-dsa/en/for-students) to arrange appropriate compensatory measures. The request must be submitted to the professor at least 15 days before the exam date. The professor will assess the suitability of the proposed measures in relation to the course's learning objectives.
Teaching tools
The slides and scientific articles presented in class will be made available to students on the university's online platform, along with other selected teaching materials.
Office hours
See the website of Jacopo Lenzi