Although specific sciences have their methodological differences, there is a general scientific method that applies to them all. While some aspects of it are well-known, others are not. Here’s a summary:
- Specify a chunk of reality to focus on. It must be remembered that each science cuts off an aspect of reality.
- Gather data about the chunk of reality. It is often assumed that an hypothesis is needed to gather data, but that is not true. All that is needed is a focus on some aspect of reality. One may possibly find data already gathered rather than undertaking some original data collection.
- Model the data gathered, that is, practice induction, which includes some data fitting, some generalization, and some definitions (new or clarified). The matter about definitions is not well known but is an important part of developing a deductive model, which is the goal.
- Treat the model as given and deduce conclusions from it, both old (to validate the model) and new (to expand knowledge). The latter are often called hypotheses.
- Gather more data in accordance with the previous steps and repeat the process.
Nowadays, it is considered acceptable to start with an hypothesis — any hypothesis, really — rather than starting with data and modelling data. But an hypothesis looking for data is spin, not science — it is an attempt to cherry-pick data to promote a position without considering the range of data available or potentially available.
“There is much data to support position X.” Yes, if you start with position X and look hard enough for data, you can find some to support almost any position. A political activist may use this approach to promote their policies, and a “scientific consensus.” Beware — that is spin, not science, and will not lead to genuine knowledge.