There is considerable interest in quantitatively measuring nucleic acids from single cells to small populations. The most commonly employed laboratory method is the real-time polymerase chain reaction (PCR) analyzed with the crossing point or crossing threshold (C(t)) method. Utilizing a multiwell plate reader we have performed hundreds of replicate reactions at each of a set of initial conditions whose initial number of copies span a concentration range of ten orders of magnitude. The resultant C(t) value distributions are analyzed with standard and novel statistical techniques to assess the variability/reliability of the PCR process. Our analysis supports the following conclusions. Given sufficient replicates, the mean and/or median C(t) values are statistically distinguishable and can be rank ordered across ten orders of magnitude in initial template concentration. As expected, the variances in the C(t) distributions grow as the number of initial copies declines to 1. We demonstrate that these variances are large enough to confound quantitative classification of the initial condition at low template concentrations. The data indicate that a misclassification transition is centered around 3000 initial copies of template DNA and that the transition region correlates with independent data on the thermal wear of the TAQ polymerase enzyme. We provide data that indicate that an alternative endpoint detection strategy based on the theory of well mixing and plate filling statistics is accurate below the misclassification transition where the real time method becomes unreliable.