To understand the basics of descriptive and inferential statistics in order to interpret the results of studies in the radiology field. To grasp the fundamental concepts necessary for setting up data collection aimed at statistical analysis.
The course is delivered through face-to-face lectures during the first semester of the first year. The theoretical lectures will be supplemented with practical applications using the JAMOVI software.
Variability of biological, clinical, and laboratory data.
Measurement errors.
Statistical nature of observations.
Absolute, relative, and percentage frequencies.
Data collection, organization, and representation.
Data synthesis: measures of central tendency (analytical and positional means, quantiles) and measures of dispersion.
Introduction to probability calculations: conditional probability and independence criteria, principles of addition and multiplication.
Probability distributions: Gaussian distribution.
General aspects of statistical inference: population and sample.
Confidence intervals for means and percentages.
Hypothesis testing and statistical regression models.
Statistical evaluations in diagnostic test classification.
Study designs.
The teaching material is available on Aulaweb.
It may be helpful to complement the notes and materials on the website with the textbook:
"Statistica Medica" by Martin Bland.
Ricevimento: Professor is available by appointment. For contact, please email alessio.signori@unige.it.
CRISTINA CAMPI
MAURO COSTAGLI
MASSIMO MARESCA
GIORGIO SACCHI
ALESSIO SIGNORI
MARIA PIA SORMANI (President and Coordinator of Integrated Course)
The assessment of learning is conducted through a written form, specifically multiple-choice quizzes, as part of the overall assessment of the Integrated Course to which the subject "Statistica Medica" belongs.
The student will need to demonstrate a comprehension of descriptive and inferential statistics and their application through exercises presented during the examination. Mastery of these concepts will be assessed based on the student's performance.
