11406 - Statistics for Experimental Research

Course Unit Page


This teaching activity contributes to the achievement of the Sustainable Development Goals of the UN 2030 Agenda.

Good health and well-being

Academic Year 2019/2020

Learning outcomes

At the end of the course the student will be able to understand the usefulness of the application of correct statistical tools for a research plan, to recognize the correct statistical tests to be used in the main research contexts and to correctly interpret statistical data reported in the scientific literature related to physiotherapy.

Course contents

·        Definition of statistics and its aims

·        Definition of variables and of distribution

·        How to do graphs and how to interpret them

·        Basic descriptive statistics

·        Inferential statistics: the comparison tests (ANOVA, ANCOVA, t-test, Non parametric tests)

·        Correlation statistics: bivariate analysis, univariate regression analysis, multivariate regression analysis

·        Association statistics: logistic regression

·        Prediction statistics: Cox-analysis, Survival analysis, Curves of Kaplan-Meyer

·        Diagnostics: sensibility and specificity, ROC curves

·        Systematic reviews and Meta-analysis: definitions, data interpretation


The main statistical tests will be shown pratically as output of the SPSS 21.0 statistical software





Ripoli A. Statistica medica facile. Alice nel paese del p-value.

Norman G.R., Streiner D.L. Biostatistics: The Bare Essentials, 3th edition

Ann Weaver, Stephen Goldberg. Clinical biostatistics and epidemiology made ridiculously simple. MedMaster Inc., Miami, USA, 2012

Teaching methods

Classical lectures

Demonstration of statistical analysis and graphs and table creation with SPSS 21.0

Interpretation of the obtained outputs

Assessment methods

Multiple answer quiz

Office hours

See the website of Arrigo Francesco Giuseppe Cicero