Universitat Internacional de Catalunya
Biostatistics
Teaching staff
Teachers
Responsible: Dr. Jose M Martínez-Sánchez (jmmartinez@uic.es)
Dr. Juan Carlos Martín-Sánchez (jcmartin@uic.es)
Dra. Cristina Lidón-Moyano (clidon@uic.es)
Introduction
This course is designed to train students with the tools needed to critically evaluate research articles published in medical journals. As well as, provide students with tools to enable them to develop and carry out research projects.
The methodology used in this course consists of theoretical presentations (30%) and case methods and computer laboratory practices (70%).
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
general skills
- Teamwork and responsibility.
- Ability to adapt and decision making.
specific skills
- Acquisition of skills for critical reading of the scientific literature.
- Training students to formulate research hypotheses and evaluate scientific information.
- Basic Training to develop research projects and presentations of scientific results at conferences.
- 28 - Obtaining and using epidemiological data and assess trends and risks in health related decision-making.
- 31 - Understand, critically evaluate and know how to use sources of clinical and biomedical information to obtain, organize, interpret and communicate scientific and health care information.
- 32 - Know how to use information and communication technology in clinical, therapeutic, preventive health care and research.
- 33 - Maintain and use records with patient data for later analysis, preserving the confidentiality of the data.
- 34 - Ability for critical thinking, creativity and constructive skeptisim with a focus on research within professional practice.
- 35 - Understand the importance and limitations of scientific thinking in the study, prevention and treatment of disease.
- 36 - Be able to formulate hypotheses, collect and critically evaluate information for problem solving using the scientific method.
- 37 - Acquire basic training for research.
- CB-1 - To have acquired advanced knowledge and demonstrated, within the context of highly specialised scientific and technological research, detailed comprehension based on theoretical and practical aspects and a working methodology from one or more fields of study.
- CB-2 - To know how to apply and incorporate knowledge, an understanding of it and its scientific basis and the ability to solve problems in new and loosely defined environments, including multidisciplinary contexts that include both researchers and highly specialised professionals.
- CB-3 - To know how to evaluate and select the appropriate scientific theories and precise methodologies required by their field of study to make judgements based on incomplete or limited information. Where necessary and appropriate, this includes a reflection on the ethical and social responsibility linked to the solution suggested in each case.
- CB-4 - To be able to predict and control the evolution of complex situations through the development of new and innovative working methodologies adapted to the scientific / research, technological or specific professional field, which is generally multidisciplinary, within which they undertake their activities.
- CB-6 - To have developed sufficient autonomy to participate in research projects and scientific or technological cooperation within the student’s own thematic and interdisciplinary context. This should also include a high degree of knowledge transfer.
- CTP-3 - To develop critical thinking and reasoning as well as self-assessment skills.
Learning outcomes of the subject
It is expected that students acquire the following learning outcomes:
- 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
Block 1: Introduction to Research
Introduction to Research
Research in Medicine and Health Sciences
Statistical method
Types and description of variables
Block 2: Descriptive statistics
Descriptive statistics univariate
Frequency distribution
Central tendency measures
Dispersion measures
Position measures
Graphic representation
Shape measures
Descriptive statistics bivariate
Joint frequency distributions
Marginal frequencies
Conditional frequencies
Assotiation & dependency measures
Regression line
Block 3: Statistical Inference
Statistical inference (I):
Basic concepts of probability
Statistical sample
What's infer?
Statistical inference (II):
Point estimation
Confidence Intervals
Hypothesis Tests
Difference of two proportions
Difference of two means
Block 4: Epidemiology
Introduction to Epidemiology
Types of studies:
Experimental: Clinial trial & quasi-experimentals
Observational: descriptive, cross-sectional & analytics (case-control & cohort)
Frequency measurements
Type of measures
Type of rates
Prevalence & incidence
Measures of association
Relative risk
Odds ratio
Prevalence ratio
Quality of the measures:
Internal & external validity
Types of bias
Teaching and learning activities
In person
| TRAINING ACTIVITY | METHODOLOGY | HORAS ALUMNO |
|---|---|---|
| MASTER LESSON | TEACHER'S LESSON TEACHER'S PRACTICE | 24 |
| PROBLEM BASED LEARNING | SELF LEARNING TEACHER'S PRACTICE | 6 |
| CASE METHOD | SELF LEARNING TEACHER'S PRACTICE | 8 |
| LABORATORY PRACTICE | SELF LEARNING TEACHER'S PRACTICE | 24 |
| VIRTUAL KNOWLEDGE | SELF LEARNING ON LINE | 10 |
Evaluation systems and criteria
In person
A mixed assessment, which will be held three components:
1 Continuous assessment of students (20%) based on the following criteria:
Works of different methods of case
Laboratory practices
2 Evaluation by laboratory practical exam (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 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 (30% of grade) and a multiple choice theory test (70% of grade). Students who have passed either party (practical and theoretical examination) will be retained to note the extraordinary announcement.
Bibliography and resources
Bibliography
Martínez-González MA, Sánchez-Villegas A, Faulín Fajardo FJ. Bioestadística amigable (2ª ED). Díaz de Santos. Madrid; 2006.
Gordis L. Epidemiología. 3a edición. Ediciones Hancourt S.A., 2005.
Szklo M, Nieto J. Epidemiología intermedia: Conceptos y Aplicaciones. Díaz de Santos; 2003.
Argimon Pallás JM, Jiménez Villa J. Métodos de investigación clínica y epidemiológica. 3 ed. Elsevier España S.A.: Madrid; 2004.
Further reading
Peña D. Fundamentos en Estadística. 1 ed. Alianza Editorial, S.A.: Madrid; 2001.
Rotman K. Epidemiología moderna. 1 ed. Ediciones Díaz de Santos, S.A.: Madrid; 1986.
Prieto Valiente L, Herranz Tejedor I. ¿Qué significa estadísticamente significativo? 1 ed. Ediciones Díaz de Santos, S.A.: Madrid; 2005.
Piédrola Gil, et al. Medicina Preventiva y Salud Pública. 10ª Edición. Barcelona: Masson S.A.; 2001.
Evaluation period
- E1 15/01/2021 11:30h
- E2 09/07/2021 11:30h