The practice and theory of statistics has developed rapidly over the past 25 years in tandem with the greatly increased power of computers, and this has revolutionised the way in which statisticians can manipulate and yse data. 'Applied Stochastic Modelling' collates all the basic tools for statistical modelling, identifying the primary principles that are currently used.

Students who already have a background in probability, statistics and statistical inference will appreciate the author's coverage of a wide range of modelling techniques, which shows them at work both in theory and practice. Examples are drawn from a variety of application areas using the popular MATLAB software. As such the book will prove a valuable reference for statisticians, modellors, research scientists and postgraduate students.

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The practice and theory of statistics have developed rapidly over the past 25 years in tandem with the greatly increased power of computers. The advent of increased computer power has revolutionised the way in which statisticians can manipulate and analyze data. This volume collates together all the basic tools for statistical modelling, identifying the primary principles that are used.

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