Malcolm Gladwell wrote a whole book about outliers and how their surroundings helped make them successful. Clearly, he never took a statistics course. Outliers, in statistics, are bad, and so they are in our research. They skew the results giving us an unrealistic mean. This week was all about finding those outliers and getting rid of them. These outliers, for example, could be objects the LIDAR is reflecting off of, or maybe a car kicks up some dust and shows up having a really high aerosol concentration. Regardless of what it may be, we’re excluding all things that may be skewing our data. This is the first part of the puzzle, or uncovering the first layer to get to the true data we seek. So, these past few days I’ve been writing the code to accomplish this.
I briefly worked on correcting for range intensity, as well, which is the next layer to uncover, but I’m still working that part out. That’ll have to be next week I suppose.
