Teaching code

4S02633

Teacher

Maria Elisabetta Zanolin

Credits

4

Language

Italian

Scientific Disciplinary Sector (SSD)

MED/01 - MEDICAL STATISTICS

Period

LEZIONI 1° SEMESTRE 1° ANNO dal Oct 19, 2020 al Dec 23, 2020.

Lessons timetable Moodle Seminars 0

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

Learning outcomes

The course aims to introduce the basic theoretical tools of Quantitative Medicine. The course points to prepare students to:
- describe, interpret and communicate appropriately the information gathered on a collective of patients (or other experimental units);
- assess the reliability of the measurements in the biomedical field, in terms of sensitivity, specificity, accuracy and precision;
- generalize the observations collected on a limited number of subjects to the population of origin using elementary inferential techniques
- read critically the articles of the biomedical area

Program

Introduction: The purpose of the statistics in medicine.

Descriptive statistics
1) The measurement process and the different types of measurement scales
2) The statistical variables and their representation by means of frequency distributions: tables with one or two variables.
3) Graphical representation of a frequency distribution
4) Measures of position (mean, median, mode, percentiles, weighted average)
5) Measures of dispersion (range, interquartile deviation, deviation, variance, standard deviation, coefficient of variation)

Probability
1) Definitions of probability: classical, frequentist, subjectivist
2) The rules of calculation of probability: addition and product rule
3) Independent and conditional probability
4) The sensitivity and specificity of a diagnostic tool
5) ROC curves
6) Bayes theorem and its applications to differential diagnosis
7) Random variables
8) Normal Distribution
9) Population and sample. Introduction to the sampling theory
10) The sampling distribution of an estimator (sample mean)

Inferential Statistics
1) Point and interval estimates: confidence interval
2) The logic of hypothesis testing: the null and the alternative hypothesis; first and second type error; the power of a test
3) Comparison of a sample mean with a population mean: z-test and t-test
4) Comparison of two sample means: t-test for unpaired data and for paired data
5) Chi-square test
6) Correlation and regression

Examination Methods

The exam is written and consists of multiple choice tests and exercises. The answers provided in the examination will be discussed with the student.