Academic Year of Degree:
2024/25
26701 - Biostatistics
Teaching Plan Information
Academic year:
2024/25
Subject:
26701 - Biostatistics
Faculty / School:
104 - Facultad de Medicina
229 - Facultad de Ciencias de la Salud y del Deporte
Degree:
304 - Degree in Medicine
305 - Degree in Medicine
649 - Degree in Medicine
650 - Degree in Medicine
ECTS:
6.0
Year:
1
Semester:
650 - First semester
304 - Second semester
305 - Second semester
649 - First semester
Subject type:
Basic Education
Module:
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1. General information
Its inclusion as a basic subject responds to the need of students to acquire sufficient knowledge and use of this tool, both for their healthcare and research work. Applying appropriate statistical techniques to the data generated by patients and the use of all available digital means of medical information will help to optimize their knowledge and evaluate the interventions carried out, improve the comprehension of reading scientific articles of interest and use scientific evidence as an instrument in decision-making.
***We inform you that we are facing a curriculum to be extinguished. During the 2024-25 and 2025-26 academic years, this subject will be governed by the guide published in the 2023-24 academic year, with the exception of the assessment system (see point 5 og this guide).
2. Learning results
Upon completion of this subject, the student will be able to:
Know the principles of the scientific method and acquire the basic training for research activity.
Know the basic concepts of biostatistics and their application to medical sciences.
Be able to formulate hypotheses, collect and critically evaluate information for problem solving, following the scientific method.
Perform and interpret the results of a statistical analysis and reach conclusions based on the proposed objectives.
Know the different types of data and measurement scales. Handle the symbols and notations typical of statistical language in order to correctly express situations typical of the field of Medicine.
Understand the concepts of probability. Total probability theorem, the concept of independence, and Bayes' theorem. Know the evaluation of diagnostic tests.
Know the concept of random variable and the main types of discrete and continuous distributions, as well as their convergences.
Make parameter estimates for populations using confidence intervals and interpret them appropriately.
Perform hypothesis tests on parametric and non-parametric theoretical models and correctly express the plausibility of the decision made in a particular contrast.
Calculate the sample size needed to perform statistical estimation and statistical hypothesis testing, as well as the type of sampling to be performed.
Decide if there is any kind of relationship between two given quantitative variables and build the most appropriate model of dependency or association for that possible relationship.
Analyze if there is a relationship between qualitative or “categorical” variables and measure their degree of association.
Be able to design and conduct simple statistical studies using computer programs and interpret their results.
Understand and critically interpret scientific texts and statistical findings from the literatura.
3. Syllabus
Theoretical classes (30 hours)
Block I. Theoretical Foundations of Biostatistics
SCIENTIFIC METHOD. Statistical method.
DESCRIPTIVE STATISTICS. Univariate and bivariate variables.
PROBABILITY. Basic concepts. Discrete and continuous random variables.
Block II: Parametric and Non-Parametric Inference and Association Measures
ESTIMATION, sample size, and types of sampling.
HYPOTHESIS TESTING. Fundamentals. Parametric and non-parametric tests. Sample size.
ASSOCIATION MEASURES. Correlation and regression and contingency tables.
Practical Classes (26 hours).
Each theoretical topic is complemented with one or two practical sessions using free software.
Seminars on Scientific Article Analysis (4 hours).
4. Academic activities
Lecture. Will emphasize the need to introduce new concepts when their applicability is required, showing that they arise in response to problems posed by previous models. Examples and their resolution using statistical programs will be interspersed.
Practical Classes. As important as lectures, they allow more active participation from students, help reinforce theoretical knowledge, and bring them closer to solving real problems using statistical packages.
Seminars on Scientific Article Analysis. Will help understand and interpret statistical findings in medical literature.
Personalized Tutorials. At established times. By appointment.
ADD/WebCT.
5. Assessment system
NEW PLAN:
The assessment will be carried out by means of written exams: one theoretical and one practical
- Theory: it is carried out through multiple-choice questions (15 in the 1st part, 21 in the 2nd and 36 if the complete subject is examined). It is averaged with the exam grade, if more than 50% of the answers are correct and it is approved if more than 65% of the questions are correct. There are no negatives points. Its maximum score is 5 points.
- Practice: - Practice: 2 to 4 problems. The maximum score is 5 points. It is averaged with the test mark if the mark obtained in this part is ≥2.5 points.
A first partial will be held in which the subject may be eliminated (ONLY FOR THE FIRST CALL) if the average grade of theory and problems is ≥5 points.
If you have eliminated the first midterm, the final exam will only include material from the 2nd midterm.
If you have NOT eliminated the first part, the entire subject will be included in the final exam.
Final grade: 1st partial x 0.40 plus 2nd partial x 0.50 plus 1 maximum point for class participation
OLD PLAN:
A final exam will be held in which the entire subject will be included and will consist of two parts:
-Theory: Quiz questions and/or short topic.
-Practice: Problem-type and/or with computer outputs.
Note: average grade point average for theory and practice. In order to be able to average, a minimum of 4 must be rolled in each of the parts. It will be approved if the average is equal to or greater than 5.
6. Sustainable Development Goals
3 - Good Health & Well-Being
4 - Quality Education
5 - Gender Equality