A complex bottleneck is a section that has several bottlenecks with varying patterns of activation in close proximity to one another; issues of concern are the number and location of individual bottlenecks and the events associated with their activation. The usefulness of N-curve methodology for analyzing complex freeway bottlenecks was evaluated by applying it in the reanalysis of a section of southbound I-5 near San Diego, California, that had been used in a previous study. The reanalysis was based on ordinary loop detector data and considered the relationship between changes in vehicular storage in individual sections (determined by N-curve analysis) and the time series of speeds. Information provided by the N-curve analysis contributed to improved understanding of the section by establishing the existence of multiple bottlenecks in two of the sections, but its contribution was modest when compared with what had already been learned from a careful analysis of speeds. A major difficulty in applying the N-curve technique was the uncertainty of the correction of accumulated errors resulting from count biases. A simple uniform correction proved inadequate in several cases because the biases appeared to be time-dependent; other approaches to bias correction led to plausible results in some of these cases but not others, and in all cases the uncertainty of the bias corrections leads to considerable uncertainty in the queue-size estimates.