Sustainability, adopting a scientific approach to research, considers hypotheses:
- Supported by evidence or not - they are never “proven”
- Specifies variables that will be examined, including predictions about comparisons, relationships among variables, etc.
- Testable - the research design, sample size and analysis are sufficient to provide evidence for or against
- Objectively examined by unbiased research designs, selection of samples and statistical analysis, sensitivity analysis and other techniques that separate evidence for causality from random error or unmeasured, uncontrolled factors
It is especially useful to design research in which support - for or against a specific hypothesis - has similarly interesting, albeit different implications ... and to erect alternative hypotheses that predict different outcomes from a comparison or analysis.
Surprisingly, you can propose testable hypotheses that address research questions in virtually any field of Sustainability, using any good methodology.
- Proposing and testing statistical hypotheses are preferred, required sampling designs that minimize bias and ensure adequate sample size or replicates
- However, relationships among variables that influence life cycle analysis, cost-benefit analysis or other modeling can be usefully posed as hypotheses as well:
- * Profitability is more sensitive to variable x than y
- * GIS analysis of forest land will show more agricultural land has been converted from soil type x than y
- * LCA of LEED certified buildings use materials with a smaller environmental footprint