Methods
This sub-wiki deals with scientific methods.
We define Scientific Methods as follows:
- First and foremost, scientific methods produce knowledge.
- Focussing on the academic perspective, scientific methods can be either reproducible and learnable; can be documented and are learnable; or are reproducible, can be documented, and are learnable.
- From a systematic perspective, methods are approaches that help us gather data, analyse data, and/or interpret it. Most methods refer to either one or two of these steps, and few methods refer to all three steps.
- Many specific methods can be differentiated into different schools of thinking, and many methods have finer differentiations or specifications in an often hierarchical fashion. These two factors make a fine but systematic overview of all methods an almost Herculean task, yet on a broader scale it is quite possible to gain an overview of the methodological canon of science within a few years, if you put some efforts into it. This Wiki tries to develop the baseline material for such an overview, yet can of course not replace practical application of methods and the continuous exploring of empirical studies within the scientific literature.
This Wiki describes each presented method (see below) in terms of
- its historical and disciplinary background
- its characteristics and process
- its strenghts and challenges
- everything related to normativity
- the potential future and open questions for the method
- as well as key publications and futher readings.
Also, each scientific method that is described on this Wiki is categorized according to the Wiki's underlying Design Criteria of Methods.
This means that each method fulfills one or more categories of each of the following criteria:
- Quantitative - Qualitative
- Inductive - Deductive
- Spatial scales: Individual - System - Global
- Temporal scales: Past - Present - Future
You can click on each category for more information and all the entries that belong to this category.
The following methods have been described (so far, many more are in preparation):
There is also a dedicated section on statistical analyses. You can find it here: Statistics. There, you will find guidance on the right statistical method to choose, data formats, data visualisation, and a range of R Code examples for various statistical applications.
