Degree course: 
Corso di Long single cycle degree (6 years) in MEDICINE AND SURGERY
Academic year when starting the degree: 
Academic year in which the course will be held: 
Course type: 
Basic compulsory subjects
First Semester
Standard lectures hours: 
Detail of lecture’s hours: 
Lesson (30 hours), Exercise (6 hours)


Final Examination: 

In-class test, with multiple choices questions and exercises. The exam will be organized so as to verify both the knowledge and the learning ability of the students (60%), and their ability to apply the knowledge in practical exercises (40%).

Voto Finale

The main aim of the course is to illustrate the basic elements of statistics needed to critically read and correctly interpret the results of a quantitative medical research.

Descriptive and inferential statistics are framed into the scientific knowledge process and the concept of "evidence-based medicine". Practicals will focus both on simple exercises and on the reading and understanding of the “results” section of scientific paper(s).

Scientific knowledge, inference and "evidence-based medicine" (2 hours). Descriptive statistics: frequency distribution, indices of location, symmetry and variability (6 hours). Probability: definition, proprieties, and application. Bayes’s theorem and diagnostic test accuracy. (4 hours). Binomial and normal distributions (2 hours). Inference: population and sample (2 hours). Central Limit Theorem, distribution of the sample mean. Hypothesis test and confidence interval for a population mean. Hypothesis test for 2 or more population means. Hypothesis test for proportions (12 ore). Elements of statistics for randomized clinical trials (2 hours).
Descriptive statistics (2 hours). Probability (2 hours). Reading of a paper from the scientific literature in the medical field (2 hours).

a. The process of scientific knowledge and "evidence-based medicine": how to generate and verify a hypothesis.
b. Descriptive statistics: definition of variables, frequency distribution.
c. Descriptive statistics: mode, median, mean
d. Variability and its measures: range, variance, standard deviation, variability coefficient
e. Symmetry
f. Probability: definitions and laws. Bayes's theorem and its application to diagnostic tests: sensitivity, specificity, predictive value, area under the ROC curve.
g. probability distributions: binomial and normal
h. Population and sample. Sampling methods. Distribution of the sampling mean and central limit theorem
i. Statistical inference: hypothesis test and confidence intervals
j. Inference on the mean: test Z, test t for independent samples, test t for matched samples, ANOVA
k. Inference on proportion(s): test Z, chi-square test, Fisher's exact test
l. Elements of statistical analyses for randomized clinical trials.

Stanton A. Glantz
Statistica per discipline biomediche. Sesta Edizione.

Lectures (30 hours) and practicals (6 hours).
Lesson notes available on the e-learning website

Reception of students by appointment, please contact the teacher at: