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\subsection{Intensity Statistics}  We show the colorplots for all intensity statistics in Figure ???. With the exception of the Cramer statistic, we find that these statistics exhibit the strongest sensitivities to changes in stellar mass-loss rates. As seen in their colorplots, the largest distances (given by the darkest colors) appear when any strong wind model (W1) is compared to either a weak wind model (W2) or a purely turbulent model (T).The Kurtosis and Skewness are our clearest examples of this, as they capture a sensitivity hierarchy among pairings. These statistics explicitly yield the largest distances between pairs of W1 and T, followed by pairs of W1 and W2. The sensitivity hierarchy with strong wind models is not seen in the PDF, SCF, and PCA.  The sensitivity hierarchy with strong wind models is not seen in the PDF, SCF, and PCA. Other simulation parameters appear to cause this blurring. For the PDF,we find that changes in magnetic field strength   For  thePDF, this  blurring is noticeable in comparisons between weaker wind models. In fact, some of these corresponding distances are as large as those involving W1. This does not happen in the PCA and SCF, since their distances not involving W1 are quite small. We only note blurring among the strong wind models. The Cramer Statistic is defined as a distance metric, so it we include its discussion and analysis here. As described in Yeremi et. al (2014), this statistic compares the interpoint differences between two data sets with the point differences between each individual data set. Following K16, we compute the Cramer Statistic using only the top 20(percent) of our data set's (integrated) intensity values. The statistic exhibits a behavior different from that of the other intensity statistics. As seen in its colorplot, we find very large distances between purely turbulent runs and runs with any degree of feedback. This indicates a sensitivity towards magnetic field strength.