Universitat Internacional de Catalunya
Biostatistics
Other languages of instruction: Catalan, English
Teaching staff
Introduction
The biostatistics course is oriented to enable students of the Biomedicine Degree to know the basic concepts of biostatistics, to understand it when they see them applied, to be able to apply them by themselves and to know when to do it.
With this, students will be able to elaborate the biostatistical part of a research project and critically evaluate the analyses performed for research articles in their field.
The methodology used in this course will consist of lectures, case methods and laboratory practices with computer.
Pre-course requirements
None.
Objectives
• Understand the concepts and basic statistical and epidemiological methods in health sciences
• To enable the student to perform basic biostatistical techniques with computer software specific for biostatistics.
• To train students for the critical reading of scientific articles.
Competences/Learning outcomes of the degree programme
- CB01 - Students must demonstrate that they have and understand knowledge in an area of study that is based on general secondary education, and it tends to be found at a level that, although it is based on advanced textbooks, also includes some aspects that involve knowledge from the cutting-edge of their field of study.
- CB03 - Students must have the ability to bring together and interpret significant data (normally within their area of study) to issue judgements that include a reflection on significant issues of a social, scientific and ethical nature.
- CB04 - That students can transmit information, ideas, problems and solutions to specialist and non-specialist audiences.
- CE07 - To apply statistical tools to Health Science studies.
- CG01 - To be aware of basic biological concepts and language specific to biomedical sciences and health status.
- CG11 - To be aware of basic concepts from different fields connected to biomedical sciences.
- CT01 - To develop the organisational and planning skills that are suitable in each moment.
- CT02 - To develop the ability to resolve problems.
- CT03 - To develop analytical and summarising skills.
- CT04 - To interpret experimental results and identify consistent and inconsistent elements.
- CT05 - To use the internet as a means of communication and a source of information.
- CT06 - To know how to communicate, give presentations and write up scientific reports.
- CT07 - To be capable of working in a team.
- CT08 - To reason and evaluate situations and results from a critical and constructive point of view.
- CT09 - To have the ability to develop interpersonal skills.
- CT10 - To be capable of autonomous learning.
- CT11 - To apply theoretical knowledge to practice.
- CT12 - To apply scientific method.
- CT13 - To be aware of the general and specific aspects related to the field of nutrition and ageing.
- CT14 - To respect the fundamental rights of equality between men and women, and the promotion of human rights and the values that are specific to a culture of peace and democratic values.
Learning outcomes of the subject
- Understand the basic concepts of descriptive statistics. Knowing how to apply these appropriately according to the type of variable.
- Understand the concepts of probability and probability distribution
- Understand the concept of hypothesis testing, random and systematic error and statistical significance.
- Learn proper use basic hypothesis tests.
- Know how to interpret, both statistically and clinically, the results obtained in both descriptive and inferential statistics.
- Acquire skills for database management and statistical software to analyze data.
- Know how to present the numerical results in the context of an article and / or research project.
- Know how to perform a critical reading of the statistical results presented in scientific literature as original articles, review, ....
Syllabus
1. Introduction. Basic concepts of statistics. The role of statistics in research.
2. Probability. Basic concepts of probability. Random variables. Main probability distributions.
3. Descriptive statistics. Univariate descriptive: tables, statistics and graphs. Bivariate descriptive.
4. Statistical inference. Estimators. Confidence intervals. Hypothesis testing. Univariate inference.
5. Bivariate inference. Comparison of means. Comparison of proportions. Correlation.
6. Statistical models. Linear regression. Logistic regression. Survival analysis.
7. Design of experiments. Factorial designs.
Teaching and learning activities
In person
The subject will be taught face-to-face through theoretical classes, problem sessions and practical sessions with the computer.
The theory of the subject will be presented in a rigorous way avoiding, however, an excess of formalization, which could mask the real purpose of the subject: to teach the fundamentals of statistics to biomedicals. For this reason, emphasis will be placed on conceptual clarity. In addition, students will learn the application of these concepts using statistical software.
Training activities
- Lecture, exercise resolution and computer practice: 60 h (Presenciality: 100%)
- Preparation and performance of evaluable activities: 30 h (Presenciality: 0%)
- Autonomous work of study and exercises: 60 h (Presenciality: 0 %)
Evaluation systems and criteria
In person
The evaluation has three parts:
1. Continuous assessment (25%) based on the presentation of oral and/or written work.
2. Assessment by examination of the learning of statistical software (30%).
3. Assessment by means of a theoretical test (45%).
In order to pass the course, the student must obtain an average mark of more than 5 and a minimum score of 4.5 in each of the three components of the course evaluation.
Students who do not pass the course in the ordinary exam will have an extraordinary exam in July, which will consist of a practical exam (30% of the mark) and a theoretical exam (70% of the mark). Students who have passed either part (practical and theory exams) will keep their marks for the extraordinary exam.
Important considerations:
Plagiarism, copying or any other action that could be considered cheating will result in a zero in this evaluation section. Doing so in, the exams will result in immediate failure of the subject.
In the second sitting, the grade of "Honours" cannot be obtained, so the maximum grade will be "Excellent".
No changes will be accepted in the timetable, dates of exams or in the evaluation system.
Exchange students (Erasmus and others) or repeaters will be subject to the same conditions as the rest of the students.
Bibliography and resources
Basic bibliography
Martínez-González MA, Sánchez-Villegas A, Faulín Fajardo FJ. “Bioestadística amigable”.
Peña D. “Fundamentos en Estadística”.
Sentís J, Pardell H, Alentà H, Cobo Valeri E, Canela i Soler J. Manual de bioestadística.
Daniel W. “Bioestadística: base para el análisis de las ciencias de la salud”.
Cobo E, Muñoz P, González JA, Bogorra J. “Bioestadística para no estadísticos: principios para interpretar un estudio científico”.
Box GEP, Hunter WG, Hunter JS. “Estadística para investigadores: introducción al diseño de experimentos, análisis de datos y construcción de modelos”.
Davies, TM. “The book of R. A first course in programming and statistics”.
Evaluation period
- E1 16/05/2025 A08 16:00h
- E2 30/06/2025 A04 10:00h