Principles of Scientific Methods focuses on the fundamental principles behind scientific methods. The book refers to "science" in a broad sense, including natural science, physics, mathematics, statistics, social science, political science, and engineering science. A principle is often abstract and has broad applicability while a method is usually concrete and specific. The author uses many concrete examples to explain principles and presents analogies to connect different methods or problems to arrive at a general principle or a common notion. He mainly discusses a particular method to address the great idea behind the method, not the method itself. The book shows how the principles are not only applicable to scientific research but also to our daily lives. The author explains how scientific methods are used for understanding how and why things happen, making predictions, and learning how to prevent mistakes and solve problems. Studying the principles of scientific methods is to think about thinking and to enlighten our understanding of scientific research. Scientific principles are the foundation of scientific methods. In this book, you'll see how the principles reveal the big ideas behind our scientific discoveries and reflect the fundamental beliefs and wisdoms of scientists. The principles make the scientific methods coherent and constitute the source of creativity.
Science in Perspective Philosophy of Science Theories of Truth Determinism and Free Will The Similarity Principle The Parsimony Principle Essence of Understanding Discovery or Invention Observation Experimentation Interpretation Qualitative and Quantitative Research Formal Reasoning Mathematics as Science Induction Deduction Logic Computation Mathematical Induction Thought Experiments Fitch's Knowability Paradox Incompleteness Theorem Pigeonhole Principle Proof by Contradiction Dimensional Analysis Experimentation Overview of Experimentation Experimentation in Life Science Control and Blinding Experiment Design Retrospective and Prospective Studies Validity and Integrity Confounding Factors Variation and Bias Randomization Adaptive Experiment Ethical Issues Scientific Inference The Concept of Probability Probability Distribution Evidential Measures Hypothesis Test Likelihood Principle Bayesian Reasoning Causal Space Decision Theory Statistical Modeling Data Mining Misconceptions and Pitfalls in Statistics Dynamics of Science Science as Art Evolution Devolution Classical Game Theory Evolutionary Game Theory Networks and Graph Theory Evolutionary Dynamics of Networks Brownian Motion Stochastic Decision Process Swarm Intelligence From Ancient Pictograph to Modern Graphics Controversies and Challenges Fairness of Social System Centralized and Decentralized Decisions Newcomb's Paradox The Monty Hall Dilemma The Two-Envelope Paradox Simpson's Paradox Regression to the Mean Causation, Association, Correlation, and Confounding Multiple Testing Exploratory and Confirmatory Studies Probability and Statistics Revisited Case Studies Social Genius of Animals Mendel's Genetics Experiments Pavlov's Dogs, Skinner's Box Ants That Count! Disease Outbreak and Network Chaos Technological Innovation Critical Path Analysis Revelations of the Braess Paradox Artificial Swarm Intelligence One Stone Three Birds Scaling in Biology Genetic Programming Mechanical Analogy Numerical Methods Pyramid and Ponzi Schemes Material Dating in Archaeology Molecular Design Clinical Trials Publication Bias Information and Entropy Bibliography Index
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