The aim of this new line of research in Applied Statistics is to consolidate BCAM as a reference in areas such as biostatistics, demography, environmental modeling, medical statistics, epidemiology, business analytics, and biomedical research applications involving data-driven mathematical and statistical tools. We aim to capture opportunities and challenges empowering collaboration with other research areas and groups (other BERC centers, business collaborators, Public Health institutions, government organizations, and Universities) in accessing, managing, integrating, analyzing and modeling datasets of diverse nature and complexity.
The Applied Statistics Research line at BCAM will contribute to create synergies between researchers from national and international institutions from different fields that require the use of statistical techniques for data modeling.
In particular, in the biomedical area, "Biostatistics" uses data to measure, understand and ultimately solve medical problems, by the use of statistical models and theory. Biostatistics is an exciting and versatile discipline contributing to all fields of medical research, evidence-based health care and decision-making. The increasing need of biostatistical support for the Basque Public Health Institutions, demands researchers in Biostatistics that not only support other researchers in biomedical and related sciences through statistical analyses and consulting, but specially to contribute to high-impact research, excellence, innovation and training in statistical modeling.
This initiative is also supported by the Spanish National Network of Biostatistics (BIOSTATNET), a pioneer network led by applied statisticians from different institutions with own research projects and teaching experience in Biostatistics, working closely with biomedical researchers. We also actively collaborate with the Biostatistics group at University of the Basque Country (UPV/EHU) and other national and international institutions in order to address issues of mathematical and statistical theory and methodology to improve decision-making process. We aim to highlight and increase the role of Statistics and foster collaboration with our partners and promote professional development and training in the area of Applied Statistics.
The statistical modeling methodology developed by the group deals with those aspects of the analysis of data that are not highly specific to particular fields of study. Therefore, our research provide concepts and methods that will, with suitable modification, be applicable in many fields (e.g. Economics, Business, Engineering, Demography etc ...) which demand a wide variety of data modeling and computational tools for the analysis of complex problems, particularly where a huge amount of data are collected.
Engineering & Technology
- Biosciences & Health
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