What should well-reasoned data fall within?

Well-reasoned data is characterized by its ability to fit within specific ranges and values that make sense in the context of the analysis being conducted. This means that the data should be quantitatively sound, adhering to the logical constraints of the study or problem it addresses. For instance, if analyzing temperature data, it would be unreasonable for the data to suggest temperatures outside the physically observable limits for that region or time of year.

The importance of fitting within specific ranges and values ensures that the conclusions drawn from the data are valid and reliable. Well-reasoned data should also align with the expected patterns, trends, and categories relevant to the subject area, contributing to robust analysis. Focusing on well-defined criteria enhances the integrity and applicability of the analysis undertaken.

While legal requirements, global standards, and academic theories are significant considerations in various contexts of data analysis, they are more framework guidelines rather than defining characteristics of the data itself. They help shape how data should be handled or interpreted but do not directly address the nature of the data’s coherence and reasonableness.