# MEDICAL STATISTICS cod. 21945

1° year of course - First semester
Professor
- Matteo GOLDONI
Statistica medica (MED/01)
Field
Scienze propedeutiche
Type of training activity
Basic
14 hours
of face-to-face activities
2 credits
hub: PARMA
course unit
in ITALIAN

Integrated course unit module: PHISICAL AND EXPERIMENTAL SCIENCES

## Learning objectives

After the course students should be able:
- to read a basic biomedical scientific article, undertsnding its structure;
- to manage a simple database, particularly in the field of occupational and environmental medicine;
- to do simple tests of inferential and descriptive statistics by using freeware software;
to assess the error in the physical direct and indirect measures .

## 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 mean, median, mode. The normal and non-normal distribution. Skewness and Kurtosis. Kolmogorov-Smirnov’s e Shapiro-Wilk’s tests. Elements about binomial and 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
and 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.
Difference between correlation and regression. Simple linear regression.
Correlation coefficient R. Pearson’s and Speraman’s tests. Theory of errors in the physical measurements, error propagation.

## Full programme

As reported in Contents.

## Bibliography

Classroom slides (uploaded on Elly during the course) are the reference point for the exam.
Some further reference books:
SA Glantz - Statistica per discipline biomediche - McGraw-Hill.
JR Taylor - Introduzione all'analisi degli errori - Zanichelli

## 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, particularly in the field of occupational and environmental medicine.
The course will be held through lectures to Students either in the classroom (“in presenza”) or possibly in synchronous-streaming (“in telepresenza”) on the Teams platform. Therefore, the opportunity of Student/Teacher interaction will be preserved both face to face and remotely, by the simultaneous use of the Teams platform.
Lectures will be supported by slide presentations, which will be available to students on the Elly platform (https://elly2020.medicina.unipr.it).

## Assessment methods and criteria

The verification of the achievement of module objectives is a written test (in presence or remotely), mainly consisting of open/multiple response 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.
The grade, expressed as 30/30, will be used as 1/3 in the weighted mean with physics (2/3).

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