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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 strong the strongest  sensitivities to changes in stellar mass-loss rates, while some show lesser ones to changes in magnetic field strength. rates.  The Kurtosis and Skewness statistics produce very clear sensitivities. are our clearest examples.  They yield the largest distances between strong wind models and purely turbulent ones (i.e. W1T2t0.2 and T2t0), followed by distances between strong wind models and weaker ones (i.e. W1T2t0.2 and W2T2t0.2). Furthermore, they even show smaller sensitivities between weaker wind models and turbulent ones. The individual sensitivities are not as clear in the PDF, SCF and PCA. They produce similar large distances between strong wind models and weak ones as well as strong wind models and turbulent ones. The different magnetic field strengths in our clouds appear to cause this blurring. When comparing weaker wind and purely turbulent models, the PDF exhibits relatively small difference, while the SCF and PCA show even smaller ones. We find less blurring at these smaller comparisons.   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, weonly  find large, significant very large  distances betweenruns paired with  purely turbulent ones, indicating runs and runs with any degree of feedback. This indicates  a sensitivity towards magnetic field strength under our input conditions. strength.  %Koch et al. (2015) defines the corresponding distance metrics as different types of norms.