  A galaxy's stellar mass is one of its most fundamental properties, but it
remains challenging to measure reliably. With the advent of very large optical
spectroscopic surveys, efficient methods that can make use of low
signal-to-noise spectra are needed. With this in mind, we created a new
software package for estimating effective stellar mass-to-light ratios $\log
\Upsilon^*$ that uses principal component analysis(PCA) basis set to optimize
the comparison between observed spectra and a large library of stellar
population synthesis models. In Paper I, we showed that a with a set of six PCA
basis vectors we could faithfully represent most optical spectra from the
Mapping Nearby Galaxies at APO (MaNGA) survey;and we tested the accuracy of our
M/L estimates using synthetic spectra. Here, we explore sources of systematic
error in our mass measurements by comparing our new measurements to data from
the literature. We compare our stellar mass surface density estimates to
kinematics-derived dynamical mass surface density measurements from the
DiskMass Survey and find some tension between the two which could be resolved
if the disk scale-heights used in the kinematic analysis were overestimated by
a factor of $\sim 1.5$. We formulate an aperture-corrected stellar mass catalog
for the MaNGA survey, and compare to previous stellar mass estimates based on
multi-band optical photometry, finding typical discrepancies of 0.1 dex. Using
the spatially resolved MaNGA data, we evaluate the impact of estimating total
stellar masses from spatially unresolved spectra, and we explore how the biases
that result from unresolved spectra depend upon the galaxy's dust extinction
and star formation rate. Finally, we describe a SDSS Value-Added Catalog which
will include both spatially resolved and total (aperture-corrected) stellar
masses for MaNGA galaxies.
