Sam said:
Michael,
Why didn't you say 2 seconds as opposed to the 4 seconds you mentioned. 2 seconds is better than 4, BUT NOT GOOD ENOUGH.
The definition of stopping power in the first post allows one to consider the probability of incapacitation in any time frame of interest. One could pick 10 seconds, or 4 seconds, or 2 seconds, or 1 second.
Sam said:
I don't see how you are going to quantify it any meaningful way in any case, and stay out of jail. You work something out with the comissars to use excess prisoners from the Gulag?
Once one has a definition, there are two possible approaches to quantifying things. One is to use live animal experiments. The other is the development of new techniques in Forensic Science to establish the time line of gunfights with an audio or video record. With increasing surveillance, an increasing percentage of shooting events are captured on audio and/or video.
We are working on acoustic techniques for shooting event reconstruction. Preliminary results indicate that using the acoustic signature of the bullet hit, one can determine whether the hit was the first hit to the chest, a subsequent hit to the chest, a miss, the first hit to the abdomen, a subsequent hit to the abdomen, a hit damaging major bone structure, or a peripheral hit damaging mainly muscle.
It is entirely foreseeable that we will be able to analyzing audio and video recordings of shooting events to determine the time from to incapacitation for each event.
Sam said:
How are you going to ensure uniformity of the 10K variables involved and how will that translate to something useful to me?
There are studies in many areas that determine the relative probabalities of outcomes without ensuring "uniformity of the 10K variables involved."
We make many life decisions based on the outcome of these studies.
For example, different individuals each have different genetic predispositions to cancer. Environmental factors further complicate the issue. There is a wide range of variation. This does not mean that a scientific study cannot determine the probability curve for contracting cancer after smoking Brand X for a certain number of years.
Suppose a scientific study compares the probabilities for contracting cancer after smoking Brand X for a certain number of years and smoking Brand Y for a certain number of years. In spite of complicating factors from the genetic and environmental variations in the specific cases, such a study can be done, and would constitute a valid scientific basis for concluding that Brand X creates a higher or lower cancer risk than Brand Y.
This same kind of study can conclude that exposure to sunlight increases cancer risk over time, or that certain foods can reduce the risk of certain cancers. In each case, there are broad variations in genetic and environmental factors, but sufficient numbers of data points can effectively average over these factors and understand how the variable of interest affects the outcome.
This kind of research does not claim that the outcome can be predicted for a specific individual, but only that the percentage of outcomes can be predicted for a large number of individual events. The fact that the outcome cannot be predicted for a specific individual does not mean that one cannot increase his odds of living to a ripe old age by certain choices such as quitting smoking or wearing sunscreen.
Likewise, one can increase ones chances of surviving a gunfight with a better ammo choice.
Probability theory correctly predicts that almost anyone who spends enough time and money gambling as a customer in a casino will come out on the losing end, and that the owners of the casino will come out on the winning end. The outcome of any specific bet is not predictable, but the eventual outcome of a large number of bets is predictable, and I often tell my college level statistics students that the lottery is a tax on people who are poor at math.
Most people make choices every day to do things that improve our health or safety in a probabilistic manner:
· We wear sunscreen.
· We try and quit smoking.
· We lose weight.
· We have our cholesterol checked.
· We buy a fire extinguisher.
· We check the batteries in our smoke detector.
· We investigate the safety record of a model of automobile before we buy it.
· We investigate the probabilistic failure rate of our method of contraception.
· We (females) get mammograms after a certain age.
· We (men) get prostate screenings after a certain age.
· We might even eat oat bran.
Therefore, there is similar value in seeking a probabilistic understanding of bullet effectiveness to aid in ammo selection. Research in this area also has important implications for training, shot placement, and future bullet designs.
Michael Courtney