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Long Range Hunting & Shooting
Well, I found out why Barnes Bullets "like jump" ...
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<blockquote data-quote="Hugnot" data-source="post: 2658610" data-attributes="member: 115658"><p>My simple bullet stuff number fixer came up with:</p><p></p><p>[ATTACH=full]408459[/ATTACH]</p><p></p><p>A variance of 2.0622222......E-6 is real tiny & with sensible views would be 0.000. Using a T Val of 2.145 for a 95% confidence level with 15 samples, (15 less 1), I produced an estimated high mean of .800 & low mean of .798. For a 95% confidence level it could be expected that the mean difference of bullet ogive lengths would be 0.002 or 2 thou. Replacing the 95% confidence T values with 99% confidence T Values would make little difference.</p><p></p><p>An insight to this stuff:</p><p></p><p>[URL unfurl="true"]https://www.itl.nist.gov/div898/handbook/eda/section3/eda3672.htm[/URL]</p><p></p><p>The TVal of 2.145 can be found in the table, row 14., column .975. or 1.0 - .975 = .025 on each tail of the 95% probability normal distribution curve.</p><p></p><p>Or - given a bucket of bullets from the same lot & measuring 15 bullets, assuming a normal distribution it can be estimated that the hi mean would be .800 & the low mean would be .798. The extreme spread of the data set would be .005. The variance & SD would be essentially zippo and the entire process would not provide any great surprise given the tiny differences of usually 1-2 thou. The .005 extreme spread would be dwarfed or minimized by a whole bunch of other measured bullets usually having length differences of 0-2 thou.</p><p></p><p>Running this stuff would be of interest to produce ammo for an army of 1,000's of shooters up against hordes of destructive rodents requiring .25 MOA accuracy. Diligent ammo production and quality control using statistical analyses would assure optimum results. Great economic benefits would be realized by many attendant gunsmiths in providing & replacing barrels having uniform chamber & bore dimensions.</p></blockquote><p></p>
[QUOTE="Hugnot, post: 2658610, member: 115658"] My simple bullet stuff number fixer came up with: [ATTACH type="full" alt="Screenshot (513).png"]408459[/ATTACH] A variance of 2.0622222......E-6 is real tiny & with sensible views would be 0.000. Using a T Val of 2.145 for a 95% confidence level with 15 samples, (15 less 1), I produced an estimated high mean of .800 & low mean of .798. For a 95% confidence level it could be expected that the mean difference of bullet ogive lengths would be 0.002 or 2 thou. Replacing the 95% confidence T values with 99% confidence T Values would make little difference. An insight to this stuff: [URL unfurl="true"]https://www.itl.nist.gov/div898/handbook/eda/section3/eda3672.htm[/URL] The TVal of 2.145 can be found in the table, row 14., column .975. or 1.0 - .975 = .025 on each tail of the 95% probability normal distribution curve. Or - given a bucket of bullets from the same lot & measuring 15 bullets, assuming a normal distribution it can be estimated that the hi mean would be .800 & the low mean would be .798. The extreme spread of the data set would be .005. The variance & SD would be essentially zippo and the entire process would not provide any great surprise given the tiny differences of usually 1-2 thou. The .005 extreme spread would be dwarfed or minimized by a whole bunch of other measured bullets usually having length differences of 0-2 thou. Running this stuff would be of interest to produce ammo for an army of 1,000's of shooters up against hordes of destructive rodents requiring .25 MOA accuracy. Diligent ammo production and quality control using statistical analyses would assure optimum results. Great economic benefits would be realized by many attendant gunsmiths in providing & replacing barrels having uniform chamber & bore dimensions. [/QUOTE]
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Well, I found out why Barnes Bullets "like jump" ...
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