The articles in this volume deal with the main inferential methods that can be applied to different kinds of experimental evidence. These contributions - accompanied with critical comments - by renowned scholars in the field of philosophy of science aim at removing the traditional opposition between inductivists and deductivists. They explore the different methods of explanation and justification in the sciences in different contexts and with different objectives. The volume contains contributions on methods of the sciences, especially on induction, deduction, abduction, laws, probability and explanation, ranging from logic, mathematics, natural to the social sciences. They present a highly topical pluralist re-evaluation of methodological and foundational procedures and reasoning, e.g. focusing in Bayesianism and Artificial Intelligence. They document the second international conference in Vienna on "Induction and Deduction in the Sciences" as part of the Scientific Network on "Historical and Contemporary Perspectives of Philosophy of Science in Europe", funded by the European Science Foundation (ESF).

The articles in this volume deal with the main inferential methods that can be applied to different kinds of experimental evidence. These contributions - accompanied with critical comments - by renowned scholars in the field of philosophy of science aim at removing the traditional opposition between inductivists and deductivists. They explore the different methods of explanation and justification in the sciences in different contexts and with different objectives. The volume contains contributions on methods of the sciences, especially on induction, deduction, abduction, laws, probability and explanation, ranging from logic, mathematics, natural to the social sciences. They present a highly topical pluralist re-evaluation of methodological and foundational procedures and reasoning, e.g. focusing in Bayesianism and Artificial Intelligence. They document the second international conference in Vienna on "Induction and Deduction in the Sciences" as part of the Scientific Network on "Historical and Contemporary Perspectives of Philosophy of Science in Europe", funded by the European Science Foundation (ESF).

Modern medicine is one of humankind's greatest achievements.Yet today, frequent medical errors and irreproducibility in biomedical research suggest that tremendous challenges beset it. Understanding these challenges and trying to remedy them have driven considerable and thoughtful critical analyses, but the apparent intransigence of these problems suggests a different perspective is needed. Now more than ever, when we see options and opportunities for healthcare expanding while resources are diminishing, it is extremely important that healthcare professionals practice medicine wisely. In Medical Reasoning, neurologist Erwin B. Montgomery, Jr. offers a new and vital perspective. He begins with the idea that the need for certainty in medical decision-making has been the primary driving force in medical reasoning. Doctors must routinely confront countless manifestations of symptoms, diseases, or behaviors in their patients. Therefore, either there are as many different "diseases" as there are patients or some economical set of principles and facts can be combined to explain each patient's disease. The response to this epistemic conundrum has driven medicine throughout history: the challenge is to discover principles and facts and then to develop means to apply them to each unique patient in a manner that provides certainty. This book studies the nature of medical decision making systematically and rigorously in both an analytic and historical context, addressing medicine's unique need for certainty in the face of the enormous variety of diseases and in the manifestations of the same disease in different patients. The book also examines how the social, legal, and economic circumstances in which medical decision-making occurs greatly influence the nature of medical reasoning. Medical Reasoning is essential for those at the intersection of healthcare and philosophy.

This comprehensive and balanced text has been written so that the "doing" of social research is closely and consistently linked to important social issues by using real social data. End-of-chapter discussion questions, research proposal development exercises and SPSS exercises help measure and enhance students’ understanding.

This book examines the philosophical conception of abductive reasoning as developed by Charles S. Peirce, the founder of American pragmatism. It explores the historical and systematic connections of Peirce's original ideas and debates about their interpretations. Abduction is understood in a broad sense which covers the discovery and pursuit of hypotheses and inference to the best explanation. The analysis presents fresh insights into this notion of reasoning, which derives from effects to causes or from surprising observations to explanatory theories. The author outlines some logical and AI approaches to abduction as well as studies various kinds of inverse problems in astronomy, physics, medicine, biology, and human sciences to provide examples of retroductions and abductions. The discussion covers also everyday examples with the implication of this notion in detective stories, one of Peirce’s own favorite themes. The author uses Bayesian probabilities to argue that explanatory abduction is a method of confirmation. He uses his own account of truth approximation to reformulate abduction as inference which leads to the truthlikeness of its conclusion. This allows a powerful abductive defense of scientific realism. This up-to-date survey and defense of the Peircean view of abduction may very well help researchers, students, and philosophers better understand the logic of truth-seeking.

An introductory 2001 textbook on probability and induction written by a foremost philosopher of science.

This book provides thorough guidance on various forms of data generation and analysis, presenting a model for the research process in which detailed data analysis and generalization through the development of concepts are central. Based on an inductive principle, which begins with raw data and moves towards concepts or theories through incremental deductive feedback loops, the ‘stepwise-deductive induction’ approach advanced by the author focuses on the analysis phase in research. Concentrating on creativity, structuring of analytical work, and collaborative development of generic knowledge, it seeks to enable researchers to extend their insight of a subject area without having personally to study all the data generated throughout a project. A constructive alternative to Grounded Theory, the approach advanced here is centred on qualitative research that aims at developing concepts, models, or theories on basis of a gradual paradigm to reduce complexity. As such, it will appeal to scholars and students across the social sciences with interests in methods and the analysis of qualitative data of various kinds.