Universitat Internacional de Catalunya
Biostatistics
Other languages of instruction: Catalan, English
Teaching staff
Teachers
Coordinador: Dr. Juan Carlos Martín (jcmartin@uic.es)
Introduction
The biostatistics course is oriented to enable students of the Bioengineering 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 computers.
Pre-course requirements
No previous criteria are needed to study the subject.
Objectives
- Understand the concepts and basic statistical and epidemiological methods in health sciences.
- To enable the student to perform basic biostatistical techniques with a computer software specific for biostatistics.
- To train students for critical reading of scientific articles.
Competences/Learning outcomes of the degree programme
- HB08 - Manage the acquisition, structuring, analysis and visualisation of data and information in the field of the speciality for a subsequent critical assessment of the results of this management.
- HB09 - Solve problems that may arise in the field of Bioengineering by applying mathematical knowledge (geometry, integral calculation, numerical methods and optimisation) and the general laws of mechanics and biomechanics.
Learning outcomes of the subject
-
Upon completion of this course, students will be able to:
• Classify the fundamental concepts of statistics and probability.
• Apply statistics and probability to engineering problems.
• Operate statistical and probabilistic tools with sound judgment for modeling and solving engineering-related problems.
• Apply statistics and probability to solve engineering problems through the development of models.
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 solving sessions and computer classes.
The theory of the subject will be exposed in a rigorous way avoiding, however, an excess of formalization, which could mask the true purpose of the subject: teach the fundamentals of statistics to bioengineers. For this reason, conceptual clarity will be emphasized. In addition, students will learn to apply these concepts using statistical software.
Formation activities
- Master Class, resolution of exercises and computer classes: 60 h (Presence: 100%)
- Preparation and performance of evaluable activities: 30 h (Presence: 0%)
- Autonomous study and exercise work: 60 h (Presence: 0%)
Evaluation systems and criteria
In person
The assessment has three components:
1 Continuous assessment (20%) based on the presentation of oral and written works
2 Evaluation by an exam of the learning of the statistical software (30%)
3 Evaluation by a multiple choice theory test (50%).
To pass the course the student must obtain an average grade greater than 5 and a minimum score of 4.5 in each of the three components of the assessment of the subject.
Students who fail the course in the ordinary call will have an extraordinary announcement in July that will consist of a practical examination (35% of grade) and a multiple choice theory test (65% of grade). Students who have passed either party (practical and theoretical examination) will be retained to note the extraordinary announcement.
Important considerations:
- Plagiarism, copying or any other action that may be considered cheating will be zero in that evaluation section. Besides, plagiarism during exams will mean the immediate failing of the whole subject.
- In the second-sitting exams, the maximum grade students will be able to obtain is "Excellent" (grade with honors distinction will not be posible).
- Changes of the calendar, exam dates or the evaluation system will not be accepted.
- Exchange students (Erasmus and others) or repeaters will be subjected to the same conditions as the rest of the students.
Important considerations
- Plagiarism, copying or any other form of academic dishonesty will result in a grade of zero for the corresponding component.
- If academic dishonesty is detected during an exam, it will result in the immediate failure of the course, with no chance of resitting.
- The use of artificial intelligence tools for the completion of assessment activities is strictly prohibited, except where their use is expressly authorized by the lecturer as part of the activity.
- The use or possession of electronic devices (mobile phones, smartwatches, earbuds, etc.) during exams is strictly prohibited.
Mere possession, even if the device is turned off, will be considered an attempt to cheat.
- If this occurs during the first call, it will result in the automatic failure of the exam, and the student will be required to attend the second call.
- If it occurs during the second call, it will result in the definitive failure of the course, and the student must re-enrol in the next academic year.
- No changes to the academic calendar, exam dates or evaluation system will be accepted under any circumstances.
- Exchange students (Erasmus or others) and repeaters are subject to the same evaluation and attendance conditions as all other 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 18/05/2026 A14 12:00h