STATISTICS APPLIED TO MEDICINE
cod. 1004683

Academic year 2015/16
1° year of course - Second semester
Professor
Matteo GOLDONI
Academic discipline
Statistica medica (MED/01)
Field
Discipline generali per la formazione del medico
Type of training activity
Basic
7 hours
of face-to-face activities
1 credits
hub: -
course unit
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Integrated course unit module: PHYSICAL SCIENCES

Learning objectives

The Module of Statistics Applied to Medicine is part of the Integrated Course of Physical Sciences. The main formative objective is to give to the students the basic
elements of medical statistics and biostatistics, so they can study and
understand the scientific literature and have some basic concepts for
future experimental studies to be conducted during the thesis period.
Some concrete examples from environmental and occupational medicine
will be done to better insert this module in the context of students’ field.
Finally, some examples will be shown with a program called OPENSTAT, a
freeware software specifically designed for basic statistics.

Prerequisites

Knowledge of basic mathematics, basic knowledge of English.

Course unit content

Definition of statistics. The types of biostatistical studies. Descriptive
statistics: qualitative and quantitative variables. Measures of central
tendency, dispersion, symmetry for quantitative variables. Arithmetic
m e a n ,
median, mode.
The normal and non-normal distribution. Skewness and Kurtosis.
Kolmogorov-Smirnov’s e Shapiro-Wilk’s tests. Elements about binomial
a n d
Poisson distributions.
Parametric and Non-Parametric Inferential statistics. The sampling theory
and central limit theorem. Hypothesis test on a mean. Constraints and
degrees of freedom. T-Student distribution. Repeated and independent
measures t-student test. Non-parametric test. The rank. Mann-Whitney’s
a n d
Wilkoxon’s tests. The frequency for categorical/qualitative variables. The
sampling of categorical variables. 2*2 contingency tables. Chi-square test
for independent data. Screening test: prevalence, sensitivity, specificity,
positive and negative predictive values, LR+/-.
Difference between correlation and regression. Simple linear regression.
Correlation coefficient R. Pearson’s and Speraman’s tests.

Full programme

As reported in Contents.

Bibliography

Classroom notes, any basic Statistics textbook.

Teaching methods

During the classroom lectures the topics of the module program will be
illustrated and commented. Each theory argument with mathematical
formulae will be explained with the use of simple and practice examples,
so that the student can focus his/her attention on basic concepts more
than the formulae themselves. Furthermore, the use of the software
OPENSTAT will permit to the student to repeat the statistical tests treated
during classes for a better comprehension of their use and meaning. Several
technical terms will be used both in Italian and in English, so that the
student can read on his own the international scientific literature.

Assessment methods and criteria

The verification of the achievement of module objectives is a written or
oral test, mainly consisting of open questions about the arguments
treated during the lessons. In this way, it is possible to assess the
student’s knowledge and understanding of both theory and practice
principles and their application in medical and biological field through the
use of current examples.

Other information

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2030 agenda goals for sustainable development

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