Teaching code

4S007306

Teacher

Simone Accordini

Credits

2

Language

Italian

Scientific Disciplinary Sector (SSD)

MED/01 - MEDICAL STATISTICS

Period

2 SEMESTRE PROFESSIONI SANITARIE dal Jan 7, 2025 al Sep 30, 2025.

Courses Single

Not Authorized

Lessons timetable Moodle Seminars 0

To show the organization of the course that includes this module, follow this link:  Course organization

Program

DESCRIPTIVE STATISTICS
The collection of biomedical data:
- stages of a scientific study;
- population, sample and statistical units;
- measurement process and measurement scales;
- validity, accuracy and precision of a measuring instrument.
The synthesis of biomedical data:
- univariate frequency distributions (absolute, relative, relative percentage and cumulative frequencies);
- graphical representation of a univariate frequency distribution (pie chart, bar chart, histogram and ogive);
- bivariate frequency distributions (contingency tables);
- measures of central tendency (mode, percentiles and median, simple and weighted arithmetic means);
- measures of dispersion (range, interquartile range, deviance, variance, standard deviation and coefficient of variation).
PROBABILITY
Elements of probability theory:
- sample space, elementary and compound events, logical operations on events;
- definitions of probability (classical, frequentist and subjective);
- axiomatic theory of probabilities;
- rules of probability calculation (addition and product);
- independent and conditional probabilities;
- expected events;
- probability estimates.
Random variables:
- discrete (Bernoulli distribution);
- continuous (Gauss, Student's T and chi-squared distributions);
- standardised normal deviate.
Screening tests:
- validity (sensitivity and specificity);
- performance (positive predictive value and negative predictive value).
INFERENTIAL STATISTICS
An outline of sampling theory.
Inferential tools:
- point estimation (sampling distribution of a mean and a proportion);
- interval estimation (confidence interval of a mean and a proportion);
- statistical hypothesis test (null and alternative hypotheses, test statistic, regions of rejection and non-rejection of the null hypothesis, type I and type II errors, power of a statistical test);
- statistical significance test (p-value);
- Z and Student's T tests;
- Pearson's chi-squared test.
Relationship between confidence interval and hypothesis testing.

Bibliography

Didactic methods

The teaching methods consist of frontal lessons during which the topics listed in the program are presented and discussed, exercises are solved and results of statistical analyses of biomedical data are interpreted. The didactic material (slides of the lessons, exercises with solutions) is made available to the students on the e-learning web page of the course (Moodle platform).

Learning assessment procedures

The final examination is a written test (duration of the test: 2 hours). The written test covers potentially all the topics listed in the program and is structured in groups of questions related to solving exercises and understanding the theory. Items are formulated as short answer questions and multiple-choice questions.

Evaluation criteria

The written test consists of questions related to calculate descriptive statistics and probabilities, and to perform basic inferential statistical analyses, critically using the methodological tools learnt during the course. Each question is assigned a score. The grade of the test (expressed in thirtieths) is given by the sum of the scores obtained in the individual questions. The test is considered passed if the student gains a minimum grade of 18/30.

Exam language

Italiano