Figure shows the results of using ARM+LSQ to analyze a transverse relaxation measurement of a sample of ground roasted coffee beans mixed with an equal weight of water. Results are presented as a spike plot, where the positions of the vertical spikes indicate the relaxation rates of components, and the heights of the spikes indicates the amplitudes of the contributions of those components. Component selection was based on finding the maximum number of components that yielded exclusively real-valued relaxation rates and amplitudes. A maximum of 6 components could be justified. Attempting to extract a smaller number of parameters gives components that are spaced more widely. The uncertainties in these parameters were determined using the Fisher Information Matrix as described above and in more detail in Part 2 of this report. The pseudo-continuous distributions reflect the resolution of the measurement and were found using the convolution method described in detail below. shows a case where noisier data leads to greater, more easily visualized, uncertainties.