Probability is a vital measure in numerous disciplines, from
bioinformatics and econometrics to finance/insurance and computer
science. Developed from a successful course, "Fundamental
Probability: A Computational Approach" provides an engaging and
hands-on introduction to this important topic. Whilst the theory is
explored in detail, this book also emphasises practical
applications, with the presentation of a large variety of examples
and exercises, along with generous use of computational tools.
Based on international teaching experience with students of
statistics, mathematics, finance and econometrics, the book:
Presents new, innovative material alongside the classic theory.
Goes beyond standard presentations by carefully introducing and
discussing more complex subject matter, including a richer use of
combinatorics, runs and occupancy distributions, various
multivariate sampling schemes, fat-tailed distributions, and
several basic concepts used in finance. Emphasises computational
matters and programming methods via generous use of examples in
MATLAB. Includes a large, self-contained Calculus/Analysis appendix
with derivations of all required tools, such as Leibniz' rule,
exchange of derivative and integral, Fubini's theorem, and
univariate and multivariate Taylor series. Presents over 150
end-of-chapter exercises, graded in terms of their difficulty, and
accompanied by a full set of solutions online.
This book is intended as an introduction to the theory of
probability for students in biology, mathematics, statistics,
economics, engineering, finance, and computer science who possess
the prerequisite knowledge of basic calculus and linear
algebra.
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