INFORMATICA E STATISTICA MEDICA
Module Medical Statistics
Academic Year 2024/2025 - Teacher:
ALFREDO PULVIRENTI
Expected Learning Outcomes
The course aims to acquire the main basic concepts of probability and statistics.
General teaching training objectives in terms of learning outcomes:
Knowledge and understanding: The course aims to acquire skills to students about the description of statistical data; Understand the basic terms (population, sample, variable, etc.); Calculation and presentation of frequency distributions; data description with graphical methods; Calculation of central tendency and variability indices; Understand the basis of the assessment of probability of an event and of a random variable; Acquiring concepts related to inferential statistics such as estimates for intervall confidence and hypothesis tests.
Applying knowledge and understanding: identify distributions appropriate to represent the knowledge underlying; solving problems of inferential statistics and probability.
Making judgments : Through concrete examples and case studies, the student will be able to independently develop solutions to specific problems and assess the suitability of a statistical inference problem and solution.
Communication skills: the student will acquire the necessary communication skills and expressive appropriateness in the use of technical language within the general framework of the analysis of data using statistical methods.
Learning skills: The course aims, as the goal, to provide students with the necessary theoretical and practical methods to address and solve problems independently in the statistical analysis of data.
Course Structure
The main resources made available to the student are the frontal lessons. During the lesson the lecturer will use slides and will deal with the details on the board, facing each concept step by step. To better follow the lessons, the slides used for the course are made available. The slides are not a means of study: they provide details on the topics covered in class.
Required Prerequisites
Knowledge of mathematics found in all high school curricula.
Attendance of Lessons
Attending lectures is mandatory. During the lesson all the topics will be addressed in detail and exercises and practical exercises will be carried out for each topic. During the lesson the student will have the opportunity to interact with the teacher and their colleagues to quickly overcome the difficulties related to the understanding of concepts.
Detailed Course Content
Introduction to probability and statistics: • Introduction to probability; • Events; • Definition of probability; • Conditioned events; • Bayes Theorem; • Discrete Random Variables; • Expectation, Variance, Covariance, Standard Deviation; • Bernoulli distribution; Binomial Distribution; Hypergeometric Distirbution; Negative Bionomial Distribution; Geometric Distribution; Poisson Distribution; • Continuos Random Variables; • Uniform distribution; Exponoential Distribution; Gaussian Distribution; • Examples and excercices; • Introduction to Descriptive Statitiscs; • The data, variables, variability, indeces; • Statistical Inference: parameter estimation, statistical tests; •; • Examples and excercies;
Textbook Information
Lantieri PB, Risso D, Ravera G: Statistica medica per le professioni sanitarie, II ed. McGraw-Hill
Learning Assessment
Learning Assessment Procedures
The final exam consists of a written test and an oral colloqium.
The written test consists of exercises and theoretical questions.
Those who fail the written test cannot take the oral exam. The written test can be viewed before the oral tests.
Unless otherwise communicated: the written exam takes place at 9:00
Note:
To take the exams it is mandatory to book using the appropriate form on the SMART-EDU portal.
Late bookings via email are not permitted. If no booking is made, the exam cannot be registered.
EXAMPLES OF FREQUENTLY ASKED QUESTIONS AND / OR EXERCISES
On the portal studium.unict.it will be made available exercises.
Examples of frequently asked questions and / or exercises
Available through the endnotes.
