1. What data do Hare et al use?
   They used a “reference database” of 3D bullet scans to train a statistical model.
2. In what ways do the methods used by Hare et al differ from the “traditional” methods of bullet matching? The “traditional” methods involve using a comparison microscope to match up striations of two bullets. The new methods involve a different kind of microscope and a more statistical and objective method to match bullets.
3. How do Hare et al use clustering to help perform bullet matching tasks?
   They used clustering, from what I think I understand of clustering, in graphs showing the distributions of the features that result from the algorithm about the number of consecutive non-matching and matching striae.
4. Identify one statistics and/or probability concept in the presentation that you have not heard of before. Do a little bit of research (Wikipedia is ok) and try to describe it to someone who doesn’t know about it. You don’t need to read it in its entirety, but you should also consult this paper to see if there is more detail on your chosen topic than is presented in the webinar.
   A new concept that was mentioned in both the video and the paper is the Euclidean vertical distance between surface measurements of aligned signatures, represented by an equation on page 12 of the bullet matching paper. From what I understand, the equation takes the signatures that the algorithm makes and finds the average distance between two signatures and puts a numberical value to it so it can be further used to test the probability or likelihood that the particular lands came from bullets fired from the same gun.