Universitat Internacional de Catalunya

Biostatistics

Biostatistics
6
7615
2
First semester
FB
Medicina social, habilidades de comunicación e iniciación a la investigación
Salud pública: Bioestadística
Main language of instruction: Spanish

Teaching staff


 

Teachers

Responsible: Dra. Cristina Lidón-Moyano (clidon@uic.es)

Hipólito Pérez Martín (hperez@uic.es)

Sonia de Paz Cantos (sdepaz@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 train students for critical reading of scientific articles.

Competencies

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.
  • 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

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.
  • 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

Type and description of variables

 

Block 2: Descriptive statistics

One-dimensional descriptive statistics:

Frequency distribution

Centralization measures

Dispersion measurements

Position measurements

Graphic representation

Shape measurements

Two-dimensional descriptive statistics:

Joint frequency distribution

Marginal distribution

Conditional distribution

Dependency or association measures

Regression line

 

Block 3: Statistical Inference

Sample designs

Random variables and sample distribution

Statistical inference (I):

Introduction to inference

One-dimensional statistical inference (II):

Punctual estimation

Confidence intervals

Hypothesis contrasts

Introduction to hypothesis testing

Two-dimensional statistical inference:

Difference of two proportions

Difference of two stockings

Correlation and regression line

Teaching and learning activities

In person



TRAINING ACTIVITYMETHODOLOGYHORAS 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



First call

• Continuous evaluation (30%): Works of the different methods of the case

 

 

• Final theoretical exam (70%)

 (10% extra): Voluntary activities

 

* exercises and exams will generally be deliverated via moodle.

* Minimum grade of 5 in the exam to average

  *80% compulsory assistance to practices

 

Second call

• Theoretical exam (100%)

* Minimum grade of 5 in the exam 

Bibliography and resources

OpenIntro Statistics. Third Edition. David M Diez, Christopher D Barr, and Mine Çetinkaya-Rundel.

 

Estadística aplicada a las ciencias de la salud. Joaquín Moncho Vasallo.

 

Estadística para biología y ciencias de la salud. J. Susan Milton. 

Evaluation period

E: exam date | R: revision date | 1: first session | 2: second session:
  • E1 20/01/2023 11:00h

Teaching and learning material