Looking at data after the fact without an initial hypothesis to test
isn't really scientific.
How important were the activities of these Londoners in the development of the new approaches to investigating nature that we sum up in the term "the Scientific Revolution?" A counterfactual hypothesis to test
Harkness's thesis that they were crucial might be: "If these individuals had never existed, would Newton still have been Newton?" When future scholars try to determine this, however, they will need to take into account the evidence that Harkness has presented in this book, which has already greatly expanded our knowledge of who was studying nature in late sixteenth-century England and how they were studying it.
For pure scientific purposes, here's a valid hypothesis to test
conduct a trial on secondary prevention in heart patients with a lifetime of bad habits that likely contributed to their heart disease to determine if a nutrient might provide some benefit But it's not valid to conclude from the results of that study that the nutrient doesn't work.
Consequently, there is no clear hypothesis to test
in this book.
Historically much of the research in molecular epidemiology has been opportunistic, driven by what populations were available, what samples have been collected, what could be measured in an available sample; out of that one might develop an hypothesis to test
. This was appropriate in the early stages of biomarker validation.
The hypothesis to test
is that perhaps growth never did pay for itself directly, but was "subsidized" from general tax revenue to a much greater extent than is true today.
Consequently, the first hypothesis to test is the existence of a positive association between the size of the business involved, their export ratio and their profitability.
Consequently, the second hypothesis to test is the existence of a positive link between the export ratio and profitability, confining this study solely to businesses working in a declining home market.