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This book is a tribute to Professor Pedro Gil, who created the
Department of Statistics, OR and TM at the University of Oviedo,
and a former President of the Spanish Society of Statistics and OR
(SEIO). In more than eighty original contributions, it illustrates
the extent to which Mathematics can help manage uncertainty, a
factor that is inherent to real life. Today it goes without saying
that, in order to model experiments and systems and to analyze
related outcomes and data, it is necessary to consider formal ideas
and develop scientific approaches and techniques for dealing with
uncertainty. Mathematics is crucial in this endeavor, as this book
demonstrates. As Professor Pedro Gil highlighted twenty years ago,
there are several well-known mathematical branches for this
purpose, including Mathematics of chance (Probability and
Statistics), Mathematics of communication (Information Theory), and
Mathematics of imprecision (Fuzzy Sets Theory and others). These
branches often intertwine, since different sources of uncertainty
can coexist, and they are not exhaustive. While most of the papers
presented here address the three aforementioned fields, some hail
from other Mathematical disciplines such as Operations Research;
others, in turn, put the spotlight on real-world studies and
applications. The intended audience of this book is mainly
statisticians, mathematicians and computer scientists, but
practitioners in these areas will certainly also find the book a
very interesting read.
This book is a tribute to Professor Pedro Gil, who created the
Department of Statistics, OR and TM at the University of Oviedo,
and a former President of the Spanish Society of Statistics and OR
(SEIO). In more than eighty original contributions, it illustrates
the extent to which Mathematics can help manage uncertainty, a
factor that is inherent to real life. Today it goes without saying
that, in order to model experiments and systems and to analyze
related outcomes and data, it is necessary to consider formal ideas
and develop scientific approaches and techniques for dealing with
uncertainty. Mathematics is crucial in this endeavor, as this book
demonstrates. As Professor Pedro Gil highlighted twenty years ago,
there are several well-known mathematical branches for this
purpose, including Mathematics of chance (Probability and
Statistics), Mathematics of communication (Information Theory), and
Mathematics of imprecision (Fuzzy Sets Theory and others). These
branches often intertwine, since different sources of uncertainty
can coexist, and they are not exhaustive. While most of the papers
presented here address the three aforementioned fields, some hail
from other Mathematical disciplines such as Operations Research;
others, in turn, put the spotlight on real-world studies and
applications. The intended audience of this book is mainly
statisticians, mathematicians and computer scientists, but
practitioners in these areas will certainly also find the book a
very interesting read.
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