1st Edition

Principles of Scientific Methods

By Mark Chang Copyright 2014
    247 Pages 101 B/W Illustrations
    by Chapman & Hall

    by Chapman & Hall

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    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
    Qualitative and Quantitative Research

    Formal Reasoning
    Mathematics as Science
    Logic Computation
    Mathematical Induction
    Thought Experiments
    Fitch’s Knowability Paradox
    Incompleteness Theorem
    Pigeonhole Principle
    Proof by Contradiction
    Dimensional Analysis

    Overview of Experimentation
    Experimentation in Life Science
    Control and Blinding
    Experiment Design
    Retrospective and Prospective Studies
    Validity and Integrity
    Confounding Factors
    Variation and Bias
    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
    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




    Mark Chang is vice president of biometrics at AMAG Pharmaceuticals and an adjunct professor at Boston University. Dr. Chang is an elected fellow of the American Statistical Association and a co-founder of the International Society for Biopharmaceutical Statistics. He serves on the editorial boards of statistical journals and has published seven books in biostatistics and science, including Paradoxes in Scientific Inference, Modern Issues and Methods in Biostatistics, Adaptive Design Theory and Implementation Using SAS and R, and Monte Carlo Simulation for the Pharmaceutical Industry.

    "This book is designed not only for a conceptual understanding of scientific fundamental principles behind the methods, but also to introduce some innovative applications from different fields. The book fits for a wide range of audiences who do not have any mathematics or statistics backgrounds. As written by an experienced statistician from pharmaceutical industry, the book provides an insightful overview of the current practices of experimentation and statistical inferences in pharmaceutical drug development, and also the concepts and rationales of the innovative methods beyond the pharmaceutical research and development. This is a useful reference book to inspire the readers of creative thinking by the great ideas behind the scientific methods. ... In summary, this is a useful reference book on understanding the scientific principles. This book contains a very good collection of innovative scientific methods and applications. The intuitive figures and diagrams are helpful to understand the concepts and the italic-face font for the definitions facilitates the review."
    Journal of Biopharmaceutical Statistics, 2015 

    "… the section on misconceptions and pitfalls in statistics is a must-read. … The book is at its best when discussing examples, paradoxical questions, or philosophical issues, and Chang puts good emphasis on statistics-related topics: publication bias, the Monty Hall problem, regression to the mean, and multiple testing issues all find a place for discussion."
    Significance, February 2015

    “… best used as a text for a course in the principles of scientific methods for both students in science and the humanities, and instructors could expand in their lectures on material that the book expresses in a lapidary style. Moreover, even those who use the book for self-study would find that the extra effort they may need to devote to the work would be well rewarded. Summing Up: Recommended. Lower-division undergraduates through researchers/faculty.”
    —R. Bharath, Northern Michigan University in CHOICE March 2015, Vol. 52 No. 7

    "As researchers interested in medicine, theoretical mathematical statistics can be somewhat grim and distant from professional medical activity, closer to the world of biology. However, Principles of Scientific Methods, by Mark Chang, discusses in a way comprehensible for nonmathematical professionals, the paradigms behind the methods of scientific research, such as the current mode of so called ‘evidence-based medicine’. It is an excellent work to introduce people to principles of research, with plentiful graphics."

    Journal of Applied Statistics, February 28, 2017