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I have a question for the group. Has anybody taken 2 extreme weight cases from a single date code, single vendor and milled them in half so you could see the wall thickness as well as the case head dimensions and see where the weight changes are occurring from?
If that has been done what has it shown?
David
This has always been my thoughts. But...We're talking tenths of a grain. Imagine trying to figure out where that tiny bit of brass is hiding. It may not be INSIDE the case at all, it may be the way the head and extractor notch is cut. That's why there is no definite relationship between internal capacity and weight, not to mention the fact that slight differences in case length due to expansion after firing would lead to slight differences in internal volume with no weight change.
This has always been my thoughts. But...
Wouldn't base to datum measurement being consistent on sized brass that has also been trimmed to length help in making a good volume comparison.
Thanks for strengthening my thoughts.Yes, I think you get closer to being consistent in internal volume, but again, weight can change a lot in the area behind the web and yet not change the internal volume.
I have weight sorted brass, and done a H20 sort. They do tend to follow one another, but it's only a tendency. There is no direct correlation IMOP.
But if you've found a node that is not sensitive to slight changes in propellant charge weight, something we strive to do, then little differences in internal volume should not matter.
As has been said many times, let the target tell the story.
We're talking tenths of a grain. Imagine trying to figure out where that tiny bit of brass is hiding. It may not be INSIDE the case at all, it may be the way the head and extractor notch is cut. That's why there is no definite relationship between internal capacity and weight, not to mention the fact that slight differences in case length due to expansion after firing would lead to slight differences in internal volume with no weight change.
I've read your posts on this subject which has me thinking strongly about weight sorting.This is not correct. There IS a linear relationship between case weight and case volume within a single Lot# of brass. I've posted rock solid evidence that this is true on several occasions recently. Anyone is free to choose not to believe that if they wish, but that doesn't change that fact.
The external dimensions of fired cases are extremely uniform, possibly even more so than cases that have been re-sized. The only significant source of weight variance that would not affect internal volume is in the extractor groove and the primer pocket. The extractor grooves are are machined with very uniform tolerances. The primer pockets are also very uniform in both diameter and depth. If they were not, primers would not fit the same from case to case, and primer pocket uniforming tools simply wouldn't work. Neither of those things happen, indicating the variance between primer pockets and extractor grooves is not large enough to affect the relationship between case weight versus case volume in a significant way.
On top of that, the extractor groove represents only a very small fraction of the internal volume of a case, anyhow. Any variance in the extractor groove volume between cases therefore represents an extremely small fraction of the total case volume. Whether someone believes sorting cases by weight as a surrogate to determining actual case volume is a worthwhile endeavor is is totally up to the individual. However, claiming that there is no relationship between case weight and case volume is demonstrably false and sorting cases by weight will generate more consistent internal volume than by doing nothing at all.
I've read your posts on this subject which has me thinking strongly about weight sorting.
The part that's most dreadful is the thought of measuring volume, air bubbles n all leading to inconsistencies on my behalf.
Or is weight sorting good enough?
I did grab 10 pieces of fresh lapua brass in 30 06 and only had .9 variance.
Above post not sure who without re reading stated 1 gr variance on these.
Or should I segregate by .3 on upper and lower keeping the .4 spread in middle as main batch? Same for short action?
Your empirical findings are completely believable, Ned. Exactly what we'd expect. And your research on this topic is impeccable. Just so much better than speculation and unsubstantiated theory. So at the very least, we can use the much-easier and faster weight sorting of cases rather than having to do volume sorting. A correlation of -.75 to -.90 is easily strong enough to go with the weight-sorting.
Also, lots of good suggestions for carrying out and recording the weight-sorting operation. I think I'll do this. Whether it will improve my groups, however, is unknown at this time! I guess I'll just have to do a little research of my own.
Many thanks to you all for your thought-provoking and helpful posts.
You don't need multiple regression analysis for the kinds of issues we're studying. Ned's reporting of a -.75 to -.90 Pearson correlation coefficient between case weight and case volume would be statistically significant at the .0005 level for as few as 15 cases measured twice (X = weight; Y = volume). With 100 cases, the p-value would be far smaller than that.Just out of curiosity, has anyone ever collected data on this and other debated topics and conducted a true statistical examination? I am not talking about descriptive statistics, but something like multiple regression where you are able to assign statistical significance to a variable. It seems that there are so many possible variables that could be involved (confounders) that it would take some pretty well-considered modelling to avoid spurious results. I know the target talks back to us, but if this has not been done, I am about to fire my SPSS up and do some work in the next few weeks.
If you are getting .75 and higher on a Pearson, you run the risk of colinearity. I was not talking about just using the numbers from the case volumes, but also thinking about including other factors that might prove to be predictors. We do so much to the brass as we are getting it ready, I just wonder if something might show up in a more complex analysis. As you say, sample size does not have to be that large to get an idea of what is going on. 50-75 rounds would probably be sufficient.You don't need multiple regression analysis for the kinds of issues we're studying. Ned's reporting of a -.75 to -.90 Pearson correlation coefficient between case weight and case volume would be statistically significant at the .0005 level for as few as 15 cases measured twice (X = weight; Y = volume). With 100 cases, the p-value would be far smaller than that.
The most obvious kind of inferential statistics necessary here for comparative testing is either 2-sample t-tests or analysis of variance. For example, fire 10 or 20 5-shot groups consisting of sets of 5 rounds in which the range of case weights in each set of 5 is very small--say .25 gr. Then fire 10 or 20 5-shot groups consisting of sets of 5 rounds in which the range of case weights in each set of 5 is large--say 1.5 or 2 gr. Then compute the average group size for the 10 or 20 small-variation groups and compare it to the average group size for the 10 or 20 large-variation groups. Very simple inferential statistics--a straightforward 2-sample t-test--are all that's required. If you wanted to expand the experiment to more than two conditions--say 3 conditions with (a) small-variation, (b) medium variation, and (c) large variation, then analysis of variance will provide the inferential test. I've done similar analyses with different .22 rimfire match ammunitions to determine the best ammo in my Anschutz target rifles--comparing, for example, Eley Tenex, Lapua Midas+, and RWS R50. It doesn't take enormous numbers of groups to reach the point where the significance test has sufficient power to detect real differences. Given reasonable variability in the group sizes, I've had sufficient power with 8-10 groups of each to detect significant differences.