cod. 21945

Academic year 2016/17
1° year of course - First semester
Academic discipline
Statistica medica (MED/01)
Scienze propedeutiche
Type of training activity
14 hours
of face-to-face activities
2 credits
hub: PARMA
course unit
in - - -

Integrated course unit module: PHISICAL AND EXPERIMENTAL SCIENCES

Learning objectives

The Module of Medical Statistics is part of the Integrated
Course of Physical and Experimental 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.


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.


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
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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