STATISTICS FOR RESEARCH AND TECHNOLOGY
Stampa
Enrollment year
2021/2022
2021/2022
Regulations
DM270
SECS-S/02 (STATISTICS FOR EXPERIMENTAL AND TECHNOLOGICAL RESEARCH)
Department
DEPARTMENT OF BRAIN AND BEHAVIORAL SCIENCES
Course
NEUROPHYSIOPATHOLOGY TECHNIQUES
Curriculum
PERCORSO COMUNE
Year of study
Period
(04/10/2021 - 21/01/2022)
ECTS
2
Lesson hours
16 lesson hours
Language
Italian
Activity type
WRITTEN TEST
Teacher
Prerequisites
The course is part of the basic training of students: together with Physics, Medical Statistics and Computer Science, it is a prerequisite for lessons and activities in the healthcare field. To better follow the course, the student must have attended and acquired basic skills in Medical Statistics and Biometrics.
Learning outcomes
The course gives tools for bivariate analysis and interpretation of data in healthcare area.
In detail, the course aims to develop the theoretical and practical knowledge of the most frequent inferential statistical methodologies (knowledge and comprehension), as well as the ability to correctly apply this knowledge both to new experimental situations and to published research studies (ability to apply knowledge and comprehension).
At the end of the course the student will be able to independently perform basic statistical analyses and communicate in an appropriate way the findings, as well as to understand and critically evaluate the published evidences in relation to their work context.
Course contents
Inferential statistics
- Test of hypothesis, type error I and II, p-value.
- General t-test.
- Parametric unpaired and paired t-test.
- Test on correlation coefficient.
- Chi-squared test.
- Statistical and clinical significance.
Teaching methods
The plan of the course is based on academic lectures and practical section (problem solving approach).

The course is organized in lectures and practical exercises. With the problem solving approach, learners will be introduced to the correct application of inferential analysis procedures and interpretation of results.
Practical exercises are not aimed at the application of theoretical concepts on experimental data sets, but at the interpretation / comprehension of scientific evidence deriving from the correct application of inferential statistics techniques.