STATISTICA MEDICA

Degree course: 
Corso di Long single cycle degree (6 years) in School of Dentistry
Academic year when starting the degree: 
2018/2019
Year: 
1
Academic year in which the course will be held: 
2018/2019
Course type: 
Basic compulsory subjects
Credits: 
4
Period: 
First Semester
Standard lectures hours: 
24
Detail of lecture’s hours: 
Lesson (24 hours)
Requirements: 

Math background acquired at high school level.

Final Examination: 
Orale

Multiple choice test and resolution of exercises.

Assessment: 
Voto Finale

The purpose of this course is to bring the future physicians to learn the main concepts and tools of statistics applied to medical sciences, allowing to be able to read and in some extent to critically evaluate the scientific literature, as well as to plan and actively participate in research studies. More specifically the purposes are:
a. introduce the basic concepts of controlled clinical trials and epidemiological studies; b. introduce the awareness on measurement error: random and systematic errors, and how to improve accuracy and precision of measurements;
c. introduce the concept of uncertainty in medicine by defining the role of probability and the concept of random variables and the probability distribution for the interpretation of biological phenomena; d. allow the student to be able to correctly interpret the most common statistical tests used in the medical field.

Research methods in biomedical sciences: basic elements on the scientific process in medical knowledge; study designs: from case reports to clinical trials, different strength of scientific evidences. Bias and confounding; major epidemiologic study designs; randomized controlled clinical trials.
Descriptive statistics: elements of sampling theory: definition, simple and stratified random sampling; descriptive statistics: types of variable, frequency distributions and representations. Measures of position, variability, symmetry.
Elements of probability: definition of probability, Conditional probability and independence; definition of random variable, probability distribution. Bayes’s theorem and its application to predictive value of a diagnostic test; the univariate normal distribution and its applications.
Elements of statistical inference: hypothesis testing: general theory; inference on the mean: test Z, test t; inference on proportions: test Z, chi-square, Fisher exact test; confidence intervals; basic element of analysis of variance (ANOVA) and covariance (ANCOVA).

Statistics in Medicine. T. Colton. Little, Brown and Company, Boston, Mass.

Class lessons and excercises.

Slides of the lessons are available