This concept covers the theory of adjustment of observations in surveying: because instruments, observers, and environmental conditions introduce blunders, systematic errors, and irreducible random (accidental) errors, raw field observations fail to satisfy the geometric and observation conditions required by a functional model. Adjustment is the procedure of deriving best, most-probable estimates (via corrections called residuals applied to observations) that are consistent with a functional model (the deterministic relationship the true quantities must obey) and a stochastic model (the relative precision/weighting of observations), exploiting redundant observations to both detect error and constrain a unique solution. The method of least squares defines "best" as the solution that minimizes the sum of squared residuals (weighted by observation precision when precisions differ), yielding a unique, statistically optimal adjustment; this belongs to the domain of surveying computation and adjustment theory, itself an application of statistical estimation to geometric/geodetic measurement.
This concept covers the theory of adjustment of observations in surveying: because instruments, observers, and environmental conditions introduce blunders, systematic errors, and irreducible random (…