This article presents graphical techniques for visualizing concurrency in online auctions. These include rug plots, which allow for a compact view of many simultaneous auctions while preserving the structure of individual auctions. We also use box plots, moving statistics plots, and autocorrelation plots, supplemented by statistical tests. Together, these are used to study synchronous events and to surmise trends in the data, as well as to raise new research questions. We illustrate our methods on data from eBay.com.
The article reports on a study which explored the relationship female undergraduates and student nurses experienced with their maternal and paternal grandmothers. In addition, the article identifies some of the factors closely associated with the relationship, considers the role played by grandmothers with regard to their granddaughters and examines differences in granddaughters' perceptions of maternal and paternal grandmothers. The results highlight the intimate relationship between granddaughter and grandmother. When compared to paternal grandmothers, maternal grandmothers were perceived by granddaughters to be emotionally closer, provide a greater sense of security, be more influential in shaping their beliefs and were more likely to be preferred. They were also found to play a more active role in granddaughters' lives.
Bids during an online auction arrive at unequally-spaced discrete time points. Our goal is to capture the entire continuous price-evolution function by representing it as a functional object. Various nonparametric smoothing methods exist to recover the functional object from the observed discrete bid data. Previous studies use penalized polynomial and monotone smoothing splines; however, these require the determination and storage of a large number of coefficients and often lengthy computational time. We present a family of parametric growth curves that describe the priceevolution during online auctions. This approach is parsimonious and has an appealing interpretation in the online auction context. We also provide an automated fitting algorithm that is computationally fast. Methods are illustrated using eBay data.
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