Few can imagine a world without telephones or televisions; many depend on computers and the Internet as part of daily life. Without scientific theory, these developments would not have been possible. In this exceptionally clear and engaging introduction to philosophy of science, James Ladyman explores the philosophical questions that arise when we reflect on the nature of the scientific method and the knowledge it produces. He discusses whether fundamental philosophical questions about knowledge and reality might be answered by science, and considers in detail the debate between realists and antirealists about the extent of scientific knowledge. Along the way, central topics in philosophy of science, such as the demarcation of science from non-science, induction, confirmation and falsification, the relationship between theory and observation and relativism are all addressed. Important and complex current debates over underdetermination, inference to the best explaination and the implications of radical theory change are clarified and clearly explained for those new to the subject.

A clear and engaging introduction to the philosophy of science, exploring the role of science within the broader framework of human knowledge and engagement with the world What are the central features and advantages of a scientific worldview? Why do even reasonable scientists sometimes disagree with each other? How are scientific methods different than those of other disciplines? Can science provide an objective account of reality? This is Philosophy of Science introduces the most important philosophical issues that arise within the empirical sciences. Requiring no previous background in philosophy, this reader-friendly volume covers topics ranging from traditional questions about the nature of explanation and the confirmation of theories to practical issues concerning the design of physical experiments and modeling. Incisive and accessible chapters with relevant case-studies and informative illustrations examine the function of thought experiments, discuss the realism/anti-realism debate, explore probability and theory testing, and address more challenging topics such as emergentism, measurement theory, and the manipulationist account of causation. Describes key philosophical concepts and their application in the empirical sciences Highlights past and present philosophical debates within the field Features numerous illustrations, real-world examples, and references to additional resources Includes a companion website with self-assessment exercises and instructor-only test banks Part of Wiley-Blackwell’s popular This Is Philosophy series, This is Philosophy of Science: An Introduction is an excellent textbook for STEM students with interest in the conceptual foundations of their disciplines, undergraduate philosophy majors, and general readers looking for an easy-to-read overview of the subject.

"In this new edition Samir Ikasha reviews the main themes of contemporary philosophy of science. Beginning with a brief account of the history of modern science, he asks whether there is a discernible pattern to the way scientific ideas change over time. He examines scientific inference, scientific explanation, and the debate between realist and anti-realist views of science."--

This textbook offers an introduction to the philosophy of science. It helps undergraduate students from the natural, the human and social sciences to gain an understanding of what science is, how it has developed, what its core traits are, how to distinguish between science and pseudo-science and to discover what a scientific attitude is. It argues against the common assumption that there is fundamental difference between natural and human science, with natural science being concerned with testing hypotheses and discovering natural laws, and the aim of human and some social sciences being to understand the meanings of individual and social group actions. Instead examines the similarities between the sciences and shows how the testing of hypotheses and doing interpretation/hermeneutics are similar activities. The book makes clear that lessons from natural scientists are relevant to students and scholars within the social and human sciences, and vice versa. It teaches its readers how to effectively demarcate between science and pseudo-science and sets criteria for true scientific thinking. Divided into three parts, the book first examines the question What is Science? It describes the evolution of science, defines knowledge, and explains the use of and need for hypotheses and hypothesis testing. The second half of part I deals with scientific data and observation, qualitative data and methods, and ends with a discussion of theories on the development of science. Part II offers philosophical reflections on four of the most important con cepts in science: causes, explanations, laws and models. Part III presents discussions on philosophy of mind, the relation between mind and body, value-free and value-related science, and reflections on actual trends in science.

Scientists have used models for hundreds of years as a means of describing phenomena and as a basis for further analogy. In Scientific Models in Philosophy of Science, Daniela Bailer-Jones assembles an original and comprehensive philosophical analysis of how models have been used and interpreted in both historical and contemporary contexts. Bailer-Jones delineates the many forms models can take (ranging from equations to animals; from physical objects to theoretical constructs), and how they are put to use. She examines early mechanical models employed by nineteenth-century physicists such as Kelvin and Maxwell, describes their roots in the mathematical principles of Newton and others, and compares them to contemporary mechanistic approaches. Bailer-Jones then views the use of analogy in the late nineteenth century as a means of understanding models and to link different branches of science. She reveals how analogies can also be models themselves, or can help to create them. The first half of the twentieth century saw little mention of models in the literature of logical empiricism. Focusing primarily on theory, logical empiricists believed that models were of temporary importance, flawed, and awaiting correction. The later contesting of logical empiricism, particularly the hypothetico-deductive account of theories, by philosophers such as Mary Hesse, sparked a renewed interest in the importance of models during the 1950s that continues to this day. Bailer-Jones analyzes subsequent propositions of: models as metaphors; Kuhn's concept of a paradigm; the Semantic View of theories; and the case study approaches of Cartwright and Morrison, among others. She then engages current debates on topics such as phenomena versus data, the distinctions between models and theories, the concepts of representation and realism, and the discerning of falsities in models.

This book is a balanced and up-to-date introduction to the philosophy of science. It covers all the main topics in the area, as well as introducing the student to the moral and social reality of science. The author's style is free from jargon, and although he makes use of scientific examples, these should be intelligible to those without much scientific background. At the same time the questions he raises are not merely abstract, so the book will be of interest and concern to scientists as well as philosophers. The author discusses the growth of knowledge of science, the status of scientific theories and their relationship to observational data, the extent to which scientific theories rest on unprovable paradigms, and the nature of scientific explanations. In later chapters he considers probability, scientific reductionism, the relationship between science and technology, and the relationship between scientific and other values.

By applying research in artificial intelligence to problems in the philosophy of science, Paul Thagard develops an exciting new approach to the study of scientific reasoning. This approach uses computational ideas to shed light on how scientific theories are discovered, evaluated, and used in explanations. Thagard describes a detailed computational model of problem solving and discovery that provides a conceptually rich yet rigorous alternative to accounts of scientific knowledge based on formal logic, and he uses it to illuminate such topics as the nature of concepts, hypothesis formation, analogy, and theory justification.