IBSTATB17

Introductory Biostatistics for Biologists

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   IMPORTANT DATES for this Course
   Deadline for applications: Aug 30th 2017
   Course dates: Sept 11th - Sept 15th 2017

Candidates with adequate profile will be accepted in the next 72 hours after the application, until we reach 20 participants.

Instructors:

Ana Luísa Papoila holds a degree in Mathematics (Probability and Statistics) from the Faculdade de Ciências da Universidade de Lisboa (FCUL), a Master of Science in Statistics and Optimization, from the Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa (UNL) and a PhD in Statistics and Operational Research, in the field of Probability and Statistics, from the FCUL in 2006. Since then, she is an Assistant Professor in the NOVA Medical School / Faculdade de Ciências Médicas of UNL where she coordinates and teaches several undergraduate and postgraduate courses in Biostatistics. Her main areas of research interest are Applied Health Statistics and Epidemiology. She is an integrated member of the Centro de Estatística e Aplicações da Universidade de Lisboa (CEAUL) since 2007. She is also responsible for the area of statistics of the Division of Statistics and Epidemiology from the Research Center of Centro Hospitalar de Lisboa Central. In GTPB, she has been an instructor of the IBSTAT series, since 2014.

Affiliation: NOVA Medical School / Faculdade de Ciências Médicas of UNL, Lisboa, PT

Maria Fernanda Diamantino is an Assistant Professor at the Faculdade de Ciências da Universidade de Lisboa (FCUL) where she teaches since 1989. She obtained a Master of Science in Probability and Statistics (in the epidemiology area) and her PhD in Probability and Statistics in 2008, both at FCUL. Over the years, she has taught several undergraduate statistical courses in various areas, for example, biology, chemistry, geology, mathematics and informatics. She is a collaborator member of the Centro de Estatística e Aplicações da Universidade de Lisboa (CEAUL). She has been focusing her interests in biostatistics and applied health statistics and has taught postgraduate courses in those areas. In GTPB, she has been an instructor of the IBSTAT series, since 2014.

Affiliation: Faculdade de Ciências da Universidade de Lisboa, Lisboa, PT

Course description

This is one of our "Foundations" type courses, providing a systematic and detailed review of fundamental concepts and techniques in Biostatistics. Participants can expect to go through a set of exercises that are based on biomedical problems. These exercises are preceded by short lectures that are simple to follow. The lectures are designed to provide the conceptual framework that is needed to release the training power of the exercises, not to flood the participants with formality, which will be kept to a minimum. We will make use of a highly interactive methodology, taking advantage of our well equipped Bioinformatics training room. With this approach, we expect to bring the participants to a high degree of usage independence in using the methods that we cover.
Main topics: Descriptive Statistics; Probability; Statistical Inference; Design of Experiments.
See the Detailed Program.

Target Audience

Most participants must have had one or more semester courses in Statistics in their graduate education. For some, learning Statistics has happened a long time ago, and that makes it difficult to go back and manipulate the concepts with full confidence. For others, school days were just a while ago, but using that knowledge represents a serious effort.
Opening a Statistics handbook, when you want to use Statistics righ away, is usually a painful experience, as concepts often show a less than obvious interdependence. Attending this course is a chance of revisiting those subjects in a systematic way, through a series of hands-on exercises, in a workflow that brings-in the skills in a seamless way.

Course Pre-requisites

Basic knowledge in Statistics is handy.
Elementary skills in computer usage are needed.
Basic Familiarity with the R environment will be necessary. Please follow the exercise that we provide. Install R from http://cran.r-project.org/ following the instructions.

Detailed Program

Instituto Gulbenkian de Ciência,

Apartado 14, 2781-901 Oeiras, Portugal

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Last updated:   Jun 29th 2017