Knowledge and understanding: elements of descriptive statistics, applications of probability; inferential statistics, tools necessary for a dentistry.

Ability to apply knowledge and understanding: being able to read and apply elements of Statistics to experiments and research in the field of dentistry.

Making judgements: being able to critically evaluate the results of experiments and scientific articles with the presence of data collection and analysis.

Communication skills: being able to express oneself appropriately on the basic topics of Statistics on biomedical-health applications, in particular in view of the degree thesis project.

Learning skills: being able to grasp the salient elements of new topics, in particular on research methodology and data processing in the biomedical field.

basic elements in descriptive statistics and in probability

Recall of descriptive statistics with examples and applications
Recalls of probability theory and its use in the biomedical field.
The Relative Risk and the Odds Ratio. Examples.
Gaussian data population and other main probability distributions and their properties.

Confidence intervals for means and proportions.
Significance tests.
Inferences from means.
Inferences from means and proportions: comparison between two populations.

Linear Regression Model
Logistic Regression Model
Poisson Regression Model
Introduction to survival analysis

Spreadsheet: good and bad news. Examples
Rcmdr and Jamovi: first introduction

Marc M. Triola, Mario F. Triola. Fondamenti di statistica. Per le discipline biomediche. Pearson, 2017. W.W. Daniel, C.L. Cross. Biostatistica - Concetti di base per l' analisi statistica delle scienze dell' area medico – sanitaria. EdiSES, 2019. M.Bland, Statistica Medica, Seconda Edizione, APOGEO. Michael J. Crawley. Statistics - an introduction using R. Wiley 2005 Slide dei Docenti.

INTRODUCTION
The use of the statistical method and statistical principles in clinical studies.

RECALLS OF ELEMENTS OF DESCRIPTIVE STATISTICS:
1. Data representation: tables and graphs. Absolute frequencies and relative, percentage and cumulative frequencies
2. Numerical summary measurements. Measurements of "central tendency": means, median, mode and their comparison.
3. Measures of “dispersion”: range of variation, variance, standard deviation, coefficient of variation, percentiles. The boxplots.
4. Analysis of the relationship between two variables: double-entry tables, scatter diagram, correlation.

RECALL OF ELEMENTS OF PROBABILITY CALCULATION IN BIOMEDICAL APPLICATIONS
1. Diagnostic tests
2. Measures of effects

INFERENTIAL STATISTICS
1. The problem of sampling in the speech therapy field.
2. Estimates and confidence intervals.
3. Hypothesis tests and their use in rehabilitation experiments.

DISCUSSION WITH GROUP WORK ON CRITICAL READING OF SCIENTIFIC ARTICLES

WORK FOR THE THESIS PROJECT

class lectures, work group discusssions

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Written test with 10 multiple choice questions, 3 points for each correct answer (maximum score 30), no penalty for incorrect answers.
There will also be group work in progress on the reading of scientific articles.
The evaluation grid adopted for the assessment of the written test is as follows:
- Excellent (30 - 30 cum laude): excellent knowledge of the topics, excellent analytical ability; the student is able to brilliantly apply theoretical knowledge to concrete cases.
- Very good (27 - 29): good knowledge of the subject matter, good analytical ability; the student is able to apply theoretical knowledge correctly to concrete cases.
- Good (24-26): good knowledge of the main topics, the student shows an adequate ability to apply theoretical knowledge to concrete cases.
- Satisfactory (21-23): the student does not show full mastery of the main topics of the course, although possessing the fundamental knowledge; however, he/she shows sufficient ability to apply theoretical knowledge to concrete cases.
- Sufficient (18-20): minimal knowledge of the main topics of the course, limited ability to apply theoretical knowledge to concrete cases.
- Insufficient: the student does not possess an acceptable knowledge of the content of the different topics of the syllabus.

This course explores topics closely related to one or more goals of the United Nations 2030 Agenda for Sustainable Development (SDGs)