cod. 1009783

Academic year 2023/24
1° year of course - First semester
- Matteo Charles MALVEZZI
Academic discipline
Statistica medica (MED/01)
Discipline generali per la formazione del medico
Type of training activity
30 hours
of face-to-face activities
3 credits
course unit

Learning objectives

This Medical Statistics course, aims to provide students with a solid understanding of statistical principles essential for proper interpretation of medical data. Students will develop skills in descriptive statistics, learning to construct frequency tables and graphs appropriate for different types of variables, as well as calculate and interpret measures of central tendency (mean, median, mode) and measures of dispersion (deviance, variance, standard deviation, coefficient of variation, etc). The foundations of statistical inference will be introduced, including concepts of sampling, sampling distribution, and confidence intervals. Students will learn the concepts of hypothesis testing, examining procedures for comparing means, proportions, and categorical variables. Practical skills in using Excel for data analysis and conducting statistical tests will be introduced. Additionally, the course will emphasize the importance of evidence-based medicine, providing students with the necessary skills to critically evaluate medical literature, correctly apply statistical analyses, and draw conclusions based on scientific evidence.


Knowledge of basic mathematics.

Course unit content

1. Introduction to Statistics and Data Collection
o Fundamental concepts of statistics and methods of data collection in the medical context.
2. Descriptive Statistics: Types of Variables, Frequency Distributions, Graphical Representations, Measures of Central Tendency and Dispersion
o Types of variables in the medical context and appropriate graphical representation methods.
o Construction of frequency tables and graphs suitable for different types of variables.
o Measures of central tendency (mean, median, mode) and measures of dispersion (deviance, variance, standard deviation, coefficient of variation) to assess data distribution and characteristics.
3. Accuracy and Precision of Measurements
o Evaluation of accuracy and precision in medical measurements.
4. Correlation
o Definition and interpretation of correlation.
o Calculation and interpretation of Pearson's correlation coefficient.
o Practical examples of correlation.
5. Concordance
o Definition and utility of concordance.
o Calculation of Cohen's K coefficient of concordance.
o Applications of concordance in medicine.
6. Introduction to Probability
o Fundamental concepts of probability.
o Calculation of simple and compound probabilities.
o Bayes' theorem and its applications.
7. Probability Application to Diagnostic Tests
o Sensitivity, specificity, and predictive value.
o Calculation and interpretation of diagnostic tests.
o Receiver Operating Characteristic (ROC) curves and their interpretation.
8. Gaussian Model and Central Limit Theorem
o Concept of the normal or Gaussian distribution.
o Properties and applications of the normal distribution.
o Central Limit Theorem and its implications.
9. Confidence Intervals
o Introduction to confidence intervals.
o Calculation and interpretation of confidence intervals.
o Confidence interval for the mean.
10. Student-t Distribution
o Characteristics of the Student-t distribution.
o Use of the Student-t distribution for small sample sizes.
o t-tests for paired and unpaired means.
11. Hypothesis Testing for Categorical Variables
o Chi-square test for independence between categorical variables.
12. Data analysis with Excel
o Frequency tables and graphs appropriate for variable types
o Descriptive statistics
o Hypothesis Testing
o Chisquare test for categorical variables

Full programme

To see contents.


Classroom slides (uploaded during the course) are the reference point for the exam.
Some further reference books:
- WW Daniel and CL Cross: Biostatistica, concetti di base per l’analisi statistica delle scienze dell’area medico-sanitaria, 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. Each theoretical will be explained with examples, so that the student can focus his/her attention on basic concepts. Furthermore, the use of software will enable the student to reproduce the statistical tests treated during classes for a better comprehension of their use and meaning.
Lectures will be held on-site in compliance with safety standards, provided that further instructions on the ongoing health emergency are not implemented. Supporting material will be available on the specific, student-reserved platform (Elly) and will include slide presentations, audio-video aids or video-recording of the lectures.

Assessment methods and criteria

The ascertainment of competence in the subject matter will be with a written exam. 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. 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

Other information