The issue whether an oscillation consists of (essentially) white noise or a sequence of autocorrelated observations, is treated in terms of the Box-Pierce Q-statistic based on autocorrelation functions of the oscillatory process. It is a cornerstone of conventional time series analysis. An introductory elementary numerical illustration of its utility in electrochemical science is provided via the destruction of Trimsol cutting oil waste in a commercial-scale anodic oxidation process using an aqueous Ag(II)/nitric acid electrolyte. Existence of strong autocorrelation between adjacent observations of reactant conversion is indicated by the first-order autoregressive model (AR(1)). Numerical discrepancy between two replicate test runs is moderate.
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