Biostatistics and data analysis
Learning outcomes of the course unit
By the end of the course the student will be able to:
• name and explain the basic principles of medical statistics and of epidemiology
• use the main medical statistical indicators
• program sampling
• programme the major points of a possible clinical trial
• determine if a diagnostic test is accurate
• describe the relationships among variables.
Course contents summary
Introduction to biostatistics.
Experimental design. Sampling.
Regression and correlation
Clinical and environmental epidemiology.
Survival curves and their analysis
Evaluating the health status of a population, the effectiveness of a therapy. Diagnostic tests.
Use of principal statistical software’s.
In addition, the course will have at least two lectures from a Clinical Research associate and one Epidemiologist.
• Part 1: revision of descriptive statistics with exercises with Excel or Past (trend and variability indicators, normal distribution and standardized normal distribution, confidence interval, t-Student tests, contingency table, correlation, regression analysis) and lesson on data visualization.
• Part2: Clinical trials: different phases and sampling (professionals outcomes)
• Part3: diagnostic tests from the biological and statistical point of view ( sensibility, specificity, predictive values, ROC curves ) with exercises with Excel or Past
• Part4: basis of epidemiology ( definition of differences between cause and risk, introduction to the main indicators used in epidemiology, such as odds ratio and relative risk ratio), survival curves and their analysis
Slides will be available to students before the beginning of a new topic through the platform Elly, students will need to be enrolled to the course on-line
R.Beaglehole, R. Bonita, T. Kjellström, Epidemiologia di base, Edizione italiana a cura di G. Agazzotti, Editoriale Fernando Folini, Casalnoceto, 1997.
M.L. Bacchi Reggiani, E. Baldi Cosseddu, A. Dormi. Principi di statistica ed epidemiologia, Società editrice Esculapio, 2010
Glantz, Statistica per le discipline biomediche, McGraw-Hill.
Frontal lectures, practise exercises on the PC, discussion of scientific papers given by the lecturer
Assessment methods and criteria
At the end of the course each student will receive a written exam to prepare at home, and that will be discussed in detail orally.
With respect to the Dublin’s descriptors, it will be evaluated:
• knowledge and comprehension of the topics discussed in the classroom, considering also the use of text books
• the capacity to apply the acquired knowledge to case studies, where of critical importance will be the capacity to collect data, to interpret them, and to communicate them in a clear and critical way