Elementary applications of probability theory : with an introduction to stochastic differential equations
โ Scribed by Tuckwell, Henry Clavering
- Publisher
- Chapman & Hall/CRC
- Year
- 2018
- Tongue
- English
- Leaves
- 309
- Series
- Texts in statistical science
- Edition
- Second edition
- Category
- Library
No coin nor oath required. For personal study only.
โฆ Synopsis
This book provides a clear and straightforward introduction to applications of probability theory with examples given in the biological sciences and engineering.The first chapter contains a summary of basic probability theory. Chapters two to five deal with random variables and their applications. Topics covered include geometric probability, estimation of animal and plant populations, reliability theory and Read more...
Abstract: This book provides a clear and straightforward introduction to applications of probability theory with examples given in the biological sciences and engineering.The first chapter contains a summary of basic probability theory. Chapters two to five deal with random variables and their applications. Topics covered include geometric probability, estimation of animal and plant populations, reliability theory and computer simulation. Chapter six contains a lucid account of the convergence of sequences of random variables, with emphasis on the central limit theorem and the weak law of numbers. The next four chapters introduce random processes, including random walks and Markov chains illustrated by examples in population genetics and population growth. This edition also includes two chapters which introduce, in a manifestly readable fashion, the topic of stochastic differential equations and their applications
โฆ Subjects
Probabilities.;MATHEMATICS / Applied.;MATHEMATICS / Probability & Statistics / General.
๐ SIMILAR VOLUMES
This is an introduction to probabilistic and statistical concepts necessary to understand the basic ideas and methods of stochastic differential equations. Based on measure theory, which is introduced as smoothly as possible, it provides practical skills in the use of MAPLE in the context of probabi
<p>The authors provide a fast introduction to probabilistic and statistical concepts necessary to understand the basic ideas and methods of stochastic differential equations. The book is based on measure theory which is introduced as smoothly as possible. It is intended for advanced undergraduate st
This is an introduction to probabilistic and statistical concepts necessary to understand the basic ideas and methods of stochastic differential equations. Based on measure theory, which is introduced as smoothly as possible, it provides practical skills in the use of MAPLE in the context of probabi