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Thread: Claude hits one out of the park....

  1. #1
    Member Al T.'s Avatar
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    Claude hits one out of the park....

    Bit pressed for time, but Claude Werner has his best post yet on his blog... (it ain't about rounds (spoiler))


    https://tacticalprofessor.wordpress....unds-to-carry/

  2. #2
    Chasing the Horizon RJ's Avatar
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    Very interesting stuff.

    Read it with interest.

  3. #3
    Site Supporter tanner's Avatar
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    Excellent post. Thanks for sharing.

  4. #4
    Can I pre-order the book...?
    Recovering Gun Store Commando. My Blog: The Clue Meter
    “It doesn’t matter what the problem is, the solution is always for us to give the government more money and power, while we eat less meat.”
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  5. #5
    Smoke Bomb / Ninja Vanish Chance's Avatar
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    Claude knows his stuff. Determining the metrics with which you're going to assess data is usually the most difficult part, at least for me. I look forward to reading Claude's book.
    "Sapiens dicit: 'Ignoscere divinum est, sed noli pretium plenum pro pizza sero allata solvere.'" - Michelangelo

  6. #6
    Hoplophilic doc SAWBONES's Avatar
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    I read that and appreciated it too, and will look forward to getting the book.

    Nice to see orderly and considered writing in the field of firearms use for personal defense, instead of the more typical (and too often sophomoric) "which gun, which caliber, how to shoot" stuff.
    "Therefore, since the world has still... Much good, but much less good than ill,
    And while the sun and moon endure, Luck's a chance, but trouble's sure,
    I'd face it as a wise man would, And train for ill and not for good." -- A.E. Housman

  7. #7
    Member Dropkick's Avatar
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    Claude would it be possible for you to run the numbers on multiple assailants over year for the five year period?

  8. #8
    I appreciate the approach and thoughtful analysis but I think it is a poor basis for some of his conclusions. Being pretty well-versed in the IPB and analytical processes involved in intelligence work (and having been burned a couple of times by incorrect/poor analysis), I think the analysis is incomplete. To be fair, I think a complete and thorough analysis would be a momentous under-taking on the verge of the impossible. Still, I think there are some things that were missed.

    It is also somewhat disingenuous to suggest that being prepared for a fight that does not conform to a statistical norm equates to worrying about "ninjas coming from the ceiling and face eating meth-heads." The recent Crossroads Mall attack required 10 rounds (IIRC) and to the best of my knowledge involved neither ninjas nor meth-heads.

    Examining other people's shootings/gunfights is valuable as they provide real-world examples to assess your skill set and equipment choices against. It can also help you prioritize limited resources. Using them as predictors of future engagements works right up until it does not.
    C Class shooter.

  9. #9
    Member NETim's Avatar
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    One in the pipe, good bad, indifferent?
    In a sort of ghastly simplicity we remove the organ and demand the function. We make men without chests and expect of them virtue and enterprise. We laugh at honour and are shocked to find traitors in our midst. We castrate and bid the geldings be fruitful.” ― C.S. Lewis, The Abolition of Man

  10. #10
    The R in F.A.R.T RevolverRob's Avatar
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    Quote Originally Posted by Kevin B. View Post
    I appreciate the approach and thoughtful analysis but I think it is a poor basis for some of his conclusions. Being pretty well-versed in the IPB and analytical processes involved in intelligence work (and having been burned a couple of times by incorrect/poor analysis), I think the analysis is incomplete. To be fair, I think a complete and thorough analysis would be a momentous under-taking on the verge of the impossible. Still, I think there are some things that were missed.
    What do you view as incomplete in the analysis? I assume you are discussing The Armed Citizen (TAC) study?

    It is also somewhat disingenuous to suggest that being prepared for a fight that does not conform to a statistical norm equates to worrying about "ninjas coming from the ceiling and face eating meth-heads." The recent Crossroads Mall attack required 10 rounds (IIRC) and to the best of my knowledge involved neither ninjas nor meth-heads.
    Hyperbole aside. That isn't what Claude is advocating. Instead, he provides data based on real-world incidents that indicate that round-count is one of the lesser influential factors in shooting incidents. We probably could and maybe should breakdown these data and investigate the explanatory power of each of the various factors shown. The statistical norm is a very informative metric, as is what are two standard deviations from that norm. Singular outlier events could happen, but to focus solely on those outliers is the false hope that you won't fall in the middle, which is much more probabilistic.

    Using them as predictors of future engagements works right up until it does not.
    This is a silly way of suggesting that we ignore real data. Yes a model can fail. It is, afterall, a simplification of a complex system. But to ignore the reality of data, because it might fail is akin to suggesting that you shouldn't wear a seatbelt, because once in awhile people get killed by their seatbelts. Overwhelmingly, the evidence suggests that one of a small series of outcomes is likely. If you end up outside of that range, chances of you being adequately prepared for that scenario, period, are unlikely. However, if you've adequately prepared for the series of outcomes that are likely, including ones that are a standard deviation or two from the norm, chances are quite good that you can respond, some what appropriately, to that non-model predicted outcome, simply because if it involves the same inputs as your model, you'll have most of your response wired in. - So yes you might get something that isn't predicted by the model, but it will still be partially predicted by the model, if the input factors are the same.

    Example: I can tell you, based on my model, that walking around between 50th and 66th street west of Lake Michigan, in Chicago, IL, can result in an increased mugging probability of 80% if you are walking between the hours of 11pm and 4 am. If you go walking and don't get mugged, is the model wrong?

    Conversely, if you get mugged at 10:55 pm is the model wrong?

    More importantly, if you consider the factors in the model, approximate time of day, location, your input, etc. Can you change the probabilities and is the model wrong?

    If I tell you it's not a good idea to go out walking around the neighborhood after 10-11pm and before 5 am, because people get mugged more often...that's still a valuable predictive model even if it isn't as precise as, "You'll be mugged at 10:38 PM on the corner of E. 57th and S. Woodlawn in Chicago."

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