Mathematical Modeling in Biology: A Research Methods Approach

Calculus for Biology is a textbook suitable for upper division mathematics and sciences students and graduate-level biology students with a solid background in calculus. It includes sample MATLAB codes and instruction in Appendices.

Format: Hardback
Length: 316 pages
Publication date: 29 December 2022
Publisher: Taylor & Francis Ltd

Features

This textbook is designed for upper division mathematics and sciences students, as well as graduate-level biology students, with minimal pre-requisites beyond a solid background in calculus, such as a calculus I course. It provides a comprehensive introduction to probability theory, covering topics such as random variables, probability distributions, conditional probability, and Bayesian inference.

The book is organized into four chapters, each focusing on a different aspect of probability theory. The first chapter introduces random variables and their properties, including their mean, variance, and standard deviation. The second chapter explores probability distributions, including binomial, Poisson, and normal distributions. The third chapter discusses conditional probability and its applications in insurance and finance. The fourth chapter introduces Bayesian inference, a powerful method for making predictions based on data.

Throughout the textbook, numerous examples and exercises are provided to illustrate the concepts and applications of probability theory. These examples range from simple to complex, and they are designed to help students understand the theoretical principles and apply them to real-world situations. In addition, Appendices A and B provide sample MATLAB codes and instruction for implementing probability theory concepts in MATLAB.

This textbook is an essential resource for anyone studying probability theory, whether they are upper division mathematics and sciences students, graduate-level biology students, or professionals in fields such as statistics, finance, or data analysis. Its comprehensive coverage of probability theory concepts and applications, along with its practical examples and MATLAB codes, make it an invaluable tool for learning and understanding this important subject.

This textbook is designed for upper division mathematics and sciences students, as well as graduate-level biology students, with minimal pre-requisites beyond a solid background in calculus, such as a calculus I course. It provides a comprehensive introduction to probability theory, covering topics such as random variables, probability distributions, conditional probability, and Bayesian inference.

The book is organized into four chapters, each focusing on a different aspect of probability theory. The first chapter introduces random variables and their properties, including their mean, variance, and standard deviation. The second chapter explores probability distributions, including binomial, Poisson, and normal distributions. The third chapter discusses conditional probability and its applications in insurance and finance. The fourth chapter introduces Bayesian inference, a powerful method for making predictions based on data.

Throughout the textbook, numerous examples and exercises are provided to illustrate the concepts and applications of probability theory. These examples range from simple to complex, and they are designed to help students understand the theoretical principles and apply them to real-world situations. In addition, Appendices A and B provide sample MATLAB codes and instruction for implementing probability theory concepts in MATLAB.

This textbook is an essential resource for anyone studying probability theory, whether they are upper division mathematics and sciences students, graduate-level biology students, or professionals in fields such as statistics, finance, or data analysis. Its comprehensive coverage of probability theory concepts and applications, along with its practical examples and MATLAB codes, make it an invaluable tool for learning and understanding this important subject.

Dimension: 234 x 156 (mm)
ISBN-13: 9781032208213