  Features in the primordial power spectrum have been suggested as an
explanation for glitches in the angular power spectrum of temperature
anisotropies measured by the WMAP satellite. However, these glitches might just
as well be artifacts of noise or cosmic variance. Using the effective Delta
chi^2 between the best-fit power-law spectrum and a deconvolved primordial
spectrum as a measure of "featureness" of the data, we perform a full
Monte-Carlo analysis to address the question of how significant the recovered
features are. We find that in 26% of the simulated data sets the reconstructed
spectrum yields a greater improvement in the likelihood than for the actually
observed data. While features cannot be categorically ruled out by this
analysis, and the possibility remains that simple theoretical models which
predict some of the observed features might stand up to rigorous statistical
testing, our results suggest that WMAP data are consistent with the assumption
of a featureless power-law primordial spectrum.
