All social scientists, despite their differences on many issues, ask causal questions about the world. In this anthology, Andrew P. Vayda and Bradley B. Walters set forth strategy and methods to answer those questions. The selected readings, all illuminating causal explanation for social scientists, are not only by anthropologists, sociologists, economists, and human ecologists but also by philosophers, biologists, psychologists, historians, and specialists in other fields. The essays will appeal to those doing applied research on practical problems as well as those seeking mainly to satisfy their curiosity about the causes of whatever events or types of events interest them.

All social scientists, despite their differences on many issues, ask causal questions about the world. In this anthology, Andrew P. Vayda and Bradley B. Walters set forth strategy and methods to answer those questions. The selected readings, all illuminating causal explanation for social scientists, are not only by anthropologists, sociologists, economists, and human ecologists but also by philosophers, biologists, psychologists, historians, and specialists in other fields. The essays will appeal to those doing applied research on practical problems as well as those seeking mainly to satisfy their curiosity about the causes of whatever events or types of events interest them.

This book develops the mathematical tools essential for students in the life sciences to describe interacting systems and predict their behavior. From predator-prey populations in an ecosystem, to hormone regulation within the body, the natural world abounds in dynamical systems that affect us profoundly. Complex feedback relations and counter-intuitive responses are common in nature; this book develops the quantitative skills needed to explore these interactions. Differential equations are the natural mathematical tool for quantifying change, and are the driving force throughout this book. The use of Euler's method makes nonlinear examples tractable and accessible to a broad spectrum of early-stage undergraduates, thus providing a practical alternative to the procedural approach of a traditional Calculus curriculum. Tools are developed within numerous, relevant examples, with an emphasis on the construction, evaluation, and interpretation of mathematical models throughout. Encountering these concepts in context, students learn not only quantitative techniques, but how to bridge between biological and mathematical ways of thinking. Examples range broadly, exploring the dynamics of neurons and the immune system, through to population dynamics and the Google PageRank algorithm. Each scenario relies only on an interest in the natural world; no biological expertise is assumed of student or instructor. Building on a single prerequisite of Precalculus, the book suits a two-quarter sequence for first or second year undergraduates, and meets the mathematical requirements of medical school entry. The later material provides opportunities for more advanced students in both mathematics and life sciences to revisit theoretical knowledge in a rich, real-world framework. In all cases, the focus is clear: how does the math help us understand the science?

This book develops the mathematical tools essential for students in the life sciences to describe interacting systems and predict their behavior. From predator-prey populations in an ecosystem, to hormone regulation within the body, the natural world abounds in dynamical systems that affect us profoundly. Complex feedback relations and counter-intuitive responses are common in nature; this book develops the quantitative skills needed to explore these interactions. Differential equations are the natural mathematical tool for quantifying change, and are the driving force throughout this book. The use of Euler's method makes nonlinear examples tractable and accessible to a broad spectrum of early-stage undergraduates, thus providing a practical alternative to the procedural approach of a traditional Calculus curriculum. Tools are developed within numerous, relevant examples, with an emphasis on the construction, evaluation, and interpretation of mathematical models throughout. Encountering these concepts in context, students learn not only quantitative techniques, but how to bridge between biological and mathematical ways of thinking. Examples range broadly, exploring the dynamics of neurons and the immune system, through to population dynamics and the Google PageRank algorithm. Each scenario relies only on an interest in the natural world; no biological expertise is assumed of student or instructor. Building on a single prerequisite of Precalculus, the book suits a two-quarter sequence for first or second year undergraduates, and meets the mathematical requirements of medical school entry. The later material provides opportunities for more advanced students in both mathematics and life sciences to revisit theoretical knowledge in a rich, real-world framework. In all cases, the focus is clear: how does the math help us understand the science?

"What makes one explanation better than another? How can we tell when an explanation has really answered our question? In a lively and readable discussion, Garfinkel argues that the key to understanding an explanation is to discover what question is really being answered. He then suggests criteria for a good explanation and goes on to examine some classic explanations in social and natural science."