The thesis of this book, as set forth in Chapter 1, is that there exist general principles of scientific method that are applicable to all of the sciences, but excessive specialization often causes scientists to neglect the study of these general principles, even though they undergird science's rationality and greatly influence science's efficiency and productivity. These general methodological principles involve the use of deductive and inductive logic, probability, parsimony, and hypothesis testing. Neither specialized techniques nor general principles can substitute for one another, but rather the winning combination for scientists is mastery of both.

The primary purpose of this book is to help scientists become better scientists, more creative and more productive, by fostering a deeper understanding of the general principles of scientific method. For instance, parsimonious models often can lead to greater accuracy and thereby improve decision-making, accelerate progress, and increase returns on research investments. Also, scientists can improve the statistical analyses of their data by understanding how the Bayesian and frequentist paradigms relate to different research questions and technological objectives.

The secondary purpose is to help scientists gain perspective on science's rationality and role. Every conclusion of science, when fully disclosed, involves components of three kinds: presuppositions, evidence, and logic. Accordingly, an explanation of scientific method amounts to disclosing and securing these three inputs. Also, clearly understood methods beget realistic expectations and legitimate claims.