A Primer on the Theory of Data

An accessible introduction to the Theory of Data, aligned with the published Version 7.1. The primer follows a progression from a value and the point it describes to universes, partition anchors, measure families, identity, sufficient state, transformation, and analytical lineage. Familiar examples explain why averaging correct daily averages can answer the wrong question, why an absent record does not by itself establish nonexistence or zero, and why FIRST/LAST depend on a governed analytical-point order rather than physical row order. Version 2.3 presents sufficient state through ordinary measure families and distinguishes a correct stored answer from the information required for another use. It introduces ordered selection through a daily-stock example and preserves the boundaries between analytical meaning, empirical evidence, approximation, and statistical inference. Definitions and proofs are developed in the cited Theory of Data foundation; this primer provides a first reading rather than an implementation manual.