The phrase "analytical hypothesis" is correct and usable in written English.
It can be used in contexts related to research, science, or critical thinking where a hypothesis is formed based on analysis or examination of data.
Example: "The analytical hypothesis proposed that the observed trends in the data were influenced by external factors."
Alternatives: "analytical assumption" or "analytical proposition".
First and foremost, the "peak fill-in-the-blank" represents a mindset rather than an analytical hypothesis.
This may even provide a promising analytical hypothesis about what claims about reasons mean, or reductive hypothesis about what reasons are.
Some theorists seem to think that full market clearing not only provides an unavoidable analytical hypothesis in general theories but also is a universal feature in market economies.
Systematic reviews constitute comprehensive synthesis of clinical knowledge but depend upon plausible, analytical hypothesis development for the trials reviewed.
The higher statistical precision and computational efficiency achieved by our fully analytical hypothesis tests will help biologists to perform large-scale screening of causal relations, providing a conservative rank-ordered list of promising candidate genes for further investigations.
The paper presents our analytical hypotheses and calculations, as well as experimental lighting strikes and mechanical impact settings and results.
Clinical reasoning used by physicians in daily practice presents itself as a combination of two different approaches: diagnostic pattern recognition (PR) and analytical hypothesis-based thinking [ 6].
Therefore, an analytical hypothesis-driven approach is essential for biological spectroscopic studies of brain tissue, with careful consideration of the biochemical alterations that are likely to occur during all stages of sample preparation.
MG: Analytical studies, hypothesis and paper elaboration.
Unlike statistical inference testing methods based on analytical null-hypothesis distributions, network centrality scores and Relief-F scores lack an analytical null distribution.
To achieve a reliable and trustworthy CIDN, we present a framework called FACID, which leverages data analytical models and hypothesis testing methods for efficient, distributed and sequential feedback aggregations.
