G Coda
Modern science is not a simple branch of knowledge; it is unified by common objectives and values, as well as by concepts, but science is not monolithic. This chapter reviewed several ways of classifying kinds of science.
The principles of hypothesis testing and falsification formed a dominant theme in the classification. Falsification played two roles in sorting science into different bins. Falsification distinguishes science from nonscience and, within the confines of bona fide science, it's pragmatic role distinguished hypothesis-testing-based science from non-hypothesis-testing-based science. Distinctions between basic and applied science are also fundamental. Discovery Science does not employ hypothesis testing, however it leads smoothly into hypothesis testing and is, itself, based on a network of associated, implicit hypotheses. The Big and Small Science modes do not map neatly onto the Big and Little Data dichotomy, and each can be linked to Discovery Science and hypothesis-based science. Indigenous science is best seen as a form of applied science practiced by native peoples.There is much more about the hypothesis that we need to cover. Generally, we haven't said why the hypothesis is beneficial, why hypothetical thinking comes so naturally to us, how it affects the Reproducibility Crisis, and related topics. Before we can move on to these broad topics, there is one more major kind of hypothesis that we need to think about: the statistical hypothesis. What is it and how is it related to the scientific hypothesis? What kind of statistics are we talking about? The concept of statistical hypothesis is so large and complex that it gets two chapters, which come next.