Chang Principles of Scientific Methods

1. Auflage 2014
ISBN: 978-1-4822-3810-5
Verlag: Taylor & Francis
Format: PDF
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)

E-Book, Englisch, 247 Seiten

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.

Zielgruppe

Scientists, researchers, teachers, and undergraduate and graduate students; advanced high school students.

Autoren/Hrsg.

Chang, Mark

Fachgebiete

• Mathematik | Informatik Mathematik Mathematik Allgemein Populäre Darstellungen der Mathematik
• Mathematik | Informatik Mathematik Stochastik

Inhaltsverzeichnis

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

Über Autor(innen)

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.