# MEDICAL STATISTICS cod. 21945

1° year of course - Second semester
Professor
Matteo GOLDONI
Statistica medica (MED/01)
Field
"discipline generali per la formazione dell'odontoiatra"
Type of training activity
Basic
48 hours
of face-to-face activities
4 credits
hub: PARMA
course unit
in ITALIAN

Integrated course unit module: BEHAVIOURAL SCIENCES AND SCIENTIFIC METHODOLOGY

## Learning objectives

At the end of the course students should be able: to understand the principles of biomedical research methodology; to read a biomedical scientific article understanding its structure, particularly in the field of dentistry; to manage a database with several variables; to do simple tests of descriptive, univariate and multivariate statistics by means of freeware software.

## Prerequisites

Basic knowledge of English and Mathematics.

## Course unit content

The first part of the course will introduce basic principles to do a statistic plan and an experimental design, and descriptive statistics. The following arguments will be debated: main probability distributions and the parameters that summarize data - central tendency (mean, median, mode), dispersion (variance, standard deviation), the coefficient of variation (CV), percentiles and their use. The second part of the course will be dedicated to basic principles of 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.
In the last part of the course, we will consider the analysis of variance (ANOVA) and multiple comparison tests. Then, multivariate statistics: multiple regression, logistic regression and multivariate ANOVA. Finally, some specific clinical tests will be presented: survival and ROC curves. In the last lessons, we will see the structure of a scientific article, particularly in the field of interest. We will use freeware software software: OPENSTAT-VASSARSTAT.

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## Bibliography

Classroom slides (uploaded on Elly after 2/3 of the course) are the
reference point for the exam. Some further reference books:
W.W. Daniel : Biostatistica – Ed. Edises

M.M Triola, M.F. Triola : Fondamenti di Statistica, Ed. Pearson

## Teaching methods

During the classroom lectures the topics of the module program will be illustrated and commented. Theory will be accompanied by examples and simulations that will illustrate its practical use. . Furthermore, the use of specific software will permit to do and solve directly them. 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/VASSARSTAT 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 ofclinical medicine and dentistry.

## Assessment methods and criteria

The verification of the achievement of module objectives is a written, consisting of a multiple response test about theory and outputs of statistical software/short exercises. 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, in 30/30, will weight on the basis on the number of credits of the module respect to the total number of credits of the integrate course.

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