Funia..either you stay on topic..or dont say anything at all.
Funia..either you stay on topic..or dont say anything at all.
It is not the size of a Collection in History that matters......Its the size of your Passion for it!! - Larry C
One never knows what tree roots push to the surface of what laid buried before the tree was planted - Larry C
“The farther back you can look, the farther forward you are likely to see.” - Winston Churchill
O.K I will choose topic.
Another Ant post back of two skulls.
Here are fronts of this skulls and back of third one not posted on this thread
Notice the different alloy type if you compare to this skull witch ,,heavy load on back,,
Without any deep knowledge of the ever popular 'sculls' I will suggest that for the most part the type of comparison and conclusions drawn by people from these sorts of threads (not limited to skulls alone, most any decoration) is that there is a consistent failure to understand the nature of mass production techniques or conformity to a pattern - in 99% of the cases the TR insignia and awards were extremely cheaply made by the standards of the time by a variety of very small to large firms who were making items to a general pattern which allows for deviation, especially in the non visible areas. The materials available and the demand for supply and production expansion all influence the perception of 'quality' today. These were never made for collectors nor for the prices they command now.
About all that can be learned from such limited samples as we see here, and in books is a general selection of random samples and information. The problem encountered here too often is the nature of sampling bias, too much categoric determination is made from far too small a sample. Knowing what general attributes of an original are will help, but deviations and 'anomalies' exist and these are hard to account for when determining authenticity.
http://www.uwex.edu/ces/4h/evaluatio...mplingbias.pdf
What is sampling bias?
Bias is a systematic error that can prejudice your evaluation findings in some way. So, sampling bias is consistent error that arises due to the sample selection. For example, a survey of high school students to measure teenage use of illegal drugs will be a biased sample because it does not include home schooled students or dropouts. A sample is also biased if certain members are underrepresented or overrepresented relative to others in the population.
For example, distributing a questionnaire at the end of a 3-day conference is likely to include more people who are committed to the conference so their views would be overrepresented. Interviews with people who walk by a certain location is going to over-represent healthy individuals or those who live near the location. Selecting a sample using a telephone book will underrepresented people who cannot afford a telephone, do not have a telephone, or do not list their telephone numbers.
Sampling bias can occur any time your sample is not a random sample. If it is not random, some individuals are more likely than others to be chosen. Always think very carefully about which individuals are being favored and how they differ.
Why does it matter?
Sampling bias means that the data you collect may not be accurate or represent the group. How can we know if the sample is biased? Sometimes you can identify sampling bias just by being very thoughtful and comparing the characteristics of respondents in your sample to what you know about the population in general. Think about the demographic characteristics that might have an important relationship to their answers. For example, if you know that gender is an important variable, and you know that the population includes 50% males and 50% females, then the sample needs to include the same proportions. If the sample includes 20% males, your results are likely to be biased because you don’t have enough responses from men.
What can we do about it? If you do identify differences between respondents in your sample and in the target population, be careful about how you report the results. Report the results in terms of who did respond. Don’t imply that the results apply to anyone other than those who responded.
Mr. Asterperious has made the key point in all of this and summarized in a scholarly and incisive fashion my own profound objection to this "scull" pseudo science.
My thesis is simple and it is identical to the fine essay above from my colleague in Arizona, USA: the variations we see are next to meaningless and cannot form a basis for much of any generalization at all.
I look at all the insignia I own on all my caps, and these are about seventy in number, and there are endless random variations in all the cap badges, especially of the arcane and barely visible variety
that seize the minds of some here.
To which the plain answer is contained, for instance, in contemporary photographs as well as, say, the Assmann catalog, that these things were made in various grades and also at least one
of which had a faux silver plated finish, which took a high polish. Or not.
Some were made of Buntmetall alloy and some were made of the Neusilber variety, with whatever alloy, with some silver plate or whatever.
In any case, my only interest in these is which badge is suitable for a black cap, and which is suitable for a grey cap, and which is more or
less of the era ca. pre 1939 and which post 1939.
The other distinctions strike me as incidental and or, as my colleague from Tucson says, meaningless and a reflection of sample bias.
See Assmann catalog page which details the variety of Werkstoffe and levels of finish of the same insignia.
Why this fact is always left out of these analyses baffles me. For instance, you see here that the army Hoheitszeichen as well as the Kranz/Kokarde for the peaked cap came in S E V E N (7) i.e. (2+5=7) different variations, to include
the various base metals and level of finish.
This fact still obtains in the Bw of today, where there exist Neusilber Effekten as well as alu. Effekten for insignia, which are worn separately and mixed and however.
Last edited by Friedrich-Berthold; 08-31-2014 at 06:19 PM.
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