This is Philosophy of Science An Introduction

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.

FRANZ-PETER GRIESMAIER is an Associate Professor of Philosophy at the University of Wyoming, where he teaches history and philosophy of science, philosophy of mind, logic, and epistemology. He is the author of Rationality and Epistemic Sophistication.

JEFFREY A. LOCKWOOD is a Professor of Natural Sciences & Humanities at the University of Wyoming. He worked for 15 years in scientific research and is a recipient of the Pushcart Prize and the John Burroughs award. Professor Lockwood’s work has been featured in the Best American Science and Nature Writing.

Preface ix

Acknowledgments xi

About the Companion Website xii

1 Pillars of Science: Reasons, Knowledge, and Truth 1

1.1 Epistemic Reasons 2

1.2 Reasoning from Evidence 7

1.3 Knowledge and Truth 11

1.4 Facts, Hypotheses, and Theories 12

1.5 Conclusion 17

2 Evidence, Observation, and Measurement 19

2.1 The Promises of Evidence 19

2.2 Basic Evidence and Derived Evidence 21

2.3 Measurement 26

2.4 Conclusion 31

3 Uses of Evidence 33

3.1 From Observation to Hypothesis 33

3.2 Theory Appraisal 36

3.3 The Demarcation Problem 42

3.4 Conclusion 49

4 Evidence, Rationality, and Disagreement 51

4.1 From Weak to Strong Evidence 51

4.2 Evidence and Rationality 60

4.3 Explaining Scientific Disagreement 63

4.4 Conclusion 69

5 The Nature of Probability 71

5.1 Basics of Probability 71

5.2 Interpretations of Probability 73

5.3 Probabilities as Credences 74

5.4 Epistemic Probabilities 79

5.5 Probabilities as Objective Chances 81

5.6 Probabilities and Defeasible Reasoning 84

5.7 Fallacies 86

5.8 Conclusion 87

6 Do Not Be Misled: Confounds and Controls 88

6.1 Trials and Errors 88

6.2 Treatment and Control 89

6.3 Randomization 94

6.4 Conclusion 99

7 Physical Experiments and Their Design 101

7.1 Historical Remarks 101

7.2 Setting Experimental Parameters 102

7.3 Dependent and Independent Variables 103

7.4 Learning from Experiment 106

7.5 Types of Errors: Pick Your Poison 112

7.6 Relationships between Experiment and Theory 113

7.7 Conclusion 117

8 Experimental Methods That They Don’t Teach 119

8.1 Found and Natural Experiments 119

8.2 Thought Experiments 122

8.3 The Structure and Evidential Value of Thought Experiments 133

8.4 Learning from TEs 136

8.5 The Ubiquity of Thought Experiments 139

8.6 Are Computer Simulations Thought Experiments? 141

8.7 Conclusion 142

9 Models: Useful Lies and Informative Fictions 144

9.1 The Nature of Models 146

9.2 Modelling Techniques 153

9.3 Analogies 156

9.4 Learning from Models 159

9.5 Conclusion 165

10 Causation and Causal Inference 167

10.1 What’s the Problem with Causation? 167

10.2 Hume’s Challenge 168

10.3 Causation as Mere Regularities 170

10.4 Conserved Quantities to the Rescue? 171

10.5 Causation and Manipulation 173

10.6 Conclusion 177

11 Strange Causation – Time Travel and Remote Action 179

11.1 On Influencing the Past 180

11.2 Quantum Mechanics and Locality 191

11.3 Conclusion 196

12 But Is Any of It Real? 198

12.1 Theories and Truth 198

12.2 A Map of the Views 199

12.3 Are Groups Real? 201

12.4 Laws of Nature 205

12.5 Is Everything Real Observable? 208

12.6 Realism vs. Antirealism 213

12.7 Structural Realism 218

12.8 Realism and Explanation 219

12.9 Conclusion 221

13 Explanation and Understanding 223

13.1 The Deductive-Nomological Model 224

13.2 The Causal Model 229

13.3 The Unificationist Model 231

13.4 The Pragmatic Model 234

13.5 What about Realism? 237

13.6 Conclusion 238

14 Fundamental Theories and the Organization of Science 240

14.1 The Layer Cake Model 242

14.2 Classical Reductionism 243

14.3 Functional Concepts 248

14.4 The Functional Model 250

14.5 Emergence 253

14.6 Interdisciplinary Research 257

14.7 Conclusion 259

15 Scientific Progress 262

15.1 Science and Technology 263

15.2 Goals of Science 264

15.3 Reduction in the Limit 265

15.4 How Theories Are Born 266

15.5 What Kind of Progress? 269

15.6 From Theories to Research Programmes 275

15.7 Methodological Anarchism 277

15.8 Incommensurability 279

15.9 Structural Realism and Progress 284

15.10 Conclusion 286

Index 288

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