The course aims to provide students with the basic theoretical knowledge of statistical methodology applied to biomedical sciences. In particular, the course is designed to develop: the ability to understand and interpret clinical and experimental data; knowledge of the main descriptive and inferential methods for data analysis; the ability to critically read scientific literature; the foundations for correctly applying statistical tools in clinical research. At the end of the course, students will be able to: i) Correctly describe the main types of variables and data in the biomedical field. ii) Apply statistical summary measures and graphically represent data. iii) Understand the concepts of probability and sampling. iv) Apply inferential statistical tests. v) Interpret the results of a statistical analysis and develop a critical approach to the evaluation of scientific evidence.
Teaching Methods
Frontal theoretical lectures and introduction to the use of R software
Assessment Methods
The exam will be written and will consist of exercises, multiple-choice questions, and open-ended questions. The test will last two hours. Students must demonstrate not only knowledge of statistical data analysis techniques but also the ability to interpret the obtained results.
Texts
Biostatistica.Concetti di base per l’analisi statistica delle scienze dell’area medico-sanitaria W. W. Daniel, C. L. Cross
Contents
The course is organized into frontal theoretical lectures with references to the R software, which represents the most versatile and widely used statistical program for data analysis in the scientific field. The following topics will be covered:
-STUDY DESIGN, STAGES OF SCIENTIFIC RESEARCH, CLASSIFICATION OF STUDIES AND DATA COLLECTION
-INTRODUCTION TO THE R ENVIRONMENT FOR DATA ANALYSIS (CREATION OF OBJECTS AND MATRICES, DATA MANIPULATION, IMPORT AND EXPORT OF DATA FILES)
-DESCRIPTIVE STATISTICS I (FREQUENCY DISTRIBUTIONS, MEASURES OF LOCATION AND DISPERSION)
-GRAPHICAL REPRESENTATION OF DATA WITH R
-SENSITIVITY AND SPECIFICITY OF A TEST
-PARAMETRIC AND NON-PARAMETRIC STATISTICAL TESTS (HOW AND WHEN TO USE THEM. THEORETICAL DEFINITIONS AND APPLICATIONS IN R)
-STATISTICAL INFERENCE (DIFFERENT HYPOTHESIS TESTS, THEORETICAL DEFINITIONS AND APPLICATIONS IN R)
-CORRELATION AND LINEAR AND LOGISTIC REGRESSION (THEORETICAL DEFINITIONS AND APPLICATIONS IN R)
The slides will be available on the KIRO platform.
