The phrase "a minimal hypothesis" is correct and usable in written English.
It can be used in scientific or academic contexts when referring to a hypothesis that is simple or has the least assumptions necessary to explain a phenomenon.
Example: "In our study, we propose a minimal hypothesis that suggests a direct correlation between temperature and the rate of photosynthesis."
Alternatives: "a basic hypothesis" or "a simple hypothesis".
One very natural response to the motivating examples from physics is to suggest that, when one recognizes that genuinely rival hypotheses could each be embedded in a body of theory that would be equally well supported by any available evidence, one should look for a more minimal hypothesis that will somehow "capture what is common" to the apparent alternatives.
The comparison of docking profiles for different drugs producing the same ADR allows us to exploit both evidence of binding and non-binding in building a consistent, minimal hypothesis.
Nevertheless, Occam's razor suggests that the minimal hypothesis, i.e., stimulation by self-antigen, rather than microbiota, is likely the major influence on the selection of the B-1a repertoire.
The notion of a basic truth would have to be transformed: a basic truth would now be one that belongs to a minimal set of hypotheses which allows the most efficient deduction of all the other truths of the system.
A minimal model based on this hypothesis relates specific subconductance states with the number of activated subunits (Chapman et al., 1997).
When examining our hypothesis of a minimal regulatory/promoter space, the size distributions of these promoter-less 'convergent' regions can be used as a Null expectation.
This is in line with the hypothesis that a minimal amount of light sleep continuity is necessary before sleep deepens to N3 and cycles to REM sleep [ 30, 34].
This manuscript presents a hypothesis that suggests that a minimal set of polymorphism in HLA-DQ and -DR specifies susceptibility and resistance to autoimmune diabetes.
These policies address the problem of how to reduce the number of hypotheses during the recognition process using a minimal number of queries.
The Q statistic tests the null hypothesis that all studies share a common effect size with a minimal dispersion of the effect sizes across studies.
