  We reassess the evidence that WMAP temperature maps contain a statistically
significant "cold spot" by repeating the analysis using simple circular top-hat
(disk) weights, as well as Gaussian weights of varying width. Contrary to
previous results that used Spherical Mexican Hat Wavelets, we find no
significant signal at any scale when we compare the coldest spot from our sky
to ones from simulated Gaussian random, isotropic maps. We trace this apparent
discrepancy to the fact that WMAP cold spot's temperature profile just happens
to favor the particular profile given by the wavelet. Since randomly generated
maps typically do not exhibit this coincidence, we conclude that the original
cold spot significance originated at least partly due to a fortuitous choice of
using a particular basis of weight functions. We also examine significance of a
more general measure that returns the most significant result among several
choices of the weighting function, angular scale of the spot, and the
statistics applied, and again find a null result.
