This book provides a clear and straightforward introduction to applications of probability theory with examples given in the biological sciences, engineering, and physical, social and statistical sciences. It also introduces the topic of stochastic differential equations and their applications.
This book provides a clear and straightforward introduction to applications of probability theory with examples given in the biological sciences, engineering, and physical, social and statistical sciences. It also introduces the topic of stochastic differential equations and their applications.
1. A review of basic probability theory 2. Geometric probability 3. Some applications of the hypergeometric and Poisson distributions 4. Reliability theory 5. Simulation and random numbers 6. Convergence of sequences of random variables: The central limit theorem and the laws of large numbers 7. Simple random walks 8. Population genetics and Markov chains 9. Population growth I: Birth and death processes 10. Population Growth II: Branching Processes 11. Stochastic Processes and an Introduction to Stochastic Differential Equations 12. Diffusion processes, stochastic differential equations and applications
1. A review of basic probability theory 2. Geometric probability 3. Some applications of the hypergeometric and Poisson distributions 4. Reliability theory 5. Simulation and random numbers 6. Convergence of sequences of random variables: The central limit theorem and the laws of large numbers 7. Simple random walks 8. Population genetics and Markov chains 9. Population growth I: Birth and death processes 10. Population Growth II: Branching Processes 11. Stochastic Processes and an Introduction to Stochastic Differential Equations 12. Diffusion processes, stochastic differential equations and applications
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