anchor.diff:  * Mac Mini 2014, i7-3720QM @ 2.6 GHz, 16 GB 1600 MHz DDR3
   * Gigabyte Brix BXi7-4770R, i7-4770R @ 3.2 GHz, 16 GB 1600 MHz DDR3
   
  -[TODO]
  +[NOTE]
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   the paragraphs below were moved from above. make them match this section
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positive.code: 
  Many benchmarks and tools make the assumption that latency follows a Gaussian distribution and report only the mean and the standard deviation. Unfortunately, latency is typically multi-modal and the most important part of the distribution when it comes to *performance* are the 'outliers'. In 99% of the cases a system's latency tends to behave as we would intuitively expect. However, the leftover 1% can be worse than the all of the 99% combined. Looking at only the mean and standard deviation is a great way to ignore and be oblivious to the more systemic issues. For example, I've seen many data sets where the worst observed case was more than 1000 standard deviations away from the mean. Such stutters can become problematic when working on real robtic systems.
  
  [TODO]
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  Dave: Putting a figure up here, even if its a dummy figure showing what you mean in terms of outliers or non-gaussian, and since you mention that visual tools like histograms and percentile plots are important.
  
  
negative.code: |*Scientific Linux 6.6-rt*   |79.753.643 |0.08 ms|0.01 |0.15 ms |7
  |========
  
  [NOTE]
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  Dave: I think it would be really effective to have a figure show histograms of the actual distributions along with the classic ‘bell-curve’ gaussian with the parameters from your table. 
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