Just like we promised, we ran the script again. This is a continuation of an ebay experiment ran in December entitled "Pink Sharon Rose Depression Glass VALUES 9-20-12 to 12-18-12"
Since this particular pattern goes by multiple names, we performed two searches: one for sharon rose and one for cabbage rose. We combined the results and removed the duplications.
For Transparency, the compiled excel sheet is posted here.
*** tumblers are not segregated by tumbler size, shape, or thickness.
The small sample sizes will be remedied as the study expands over time. There will be moving data points and global averages as we get more data points next quarter.
The shipping may be included in the next study, being added to the sold price and divided with the batch prices so that the price per unit will increase appropriately. Standard deviation may also decrease
In general, the prices in general have decreased for these items, a -$0.83 overall. The published data woefully overestimates the price on average by 283%.
Let me know in the comments if you used this data for anything!
Antique
stores and estate sales aside, the most accessable way to get
depression glass is ebay. That is the basis for this study.
I know my pattern, and that is the only pattern studied. My pattern is Sharon Rose, otherwise known as Rose of Sharon or Cabbage rose by the Federal Glass Company from 1935-1939.
I know my pattern, and that is the only pattern studied. My pattern is Sharon Rose, otherwise known as Rose of Sharon or Cabbage rose by the Federal Glass Company from 1935-1939.
Alex and I wrote a script that searched ebay for all auctions within
the last three months that had the words “pink cabbage rose depression glass” or "pink sharon rose depression glass"
in any form.
Only auctions that have at least 1 bidder are used to create the average price.
The shipping is not calculated in the unit price. Price per unit is calculated manually, although
larger batches tend to have lower price per units due to this omission.
High standard deviation units may
indicate that the data points are bimodal and we may have grouped categories
that should have been segregated i.e. thick vs thin tumblers.
By the way, all tumblers regardless of size
thick or thin are grouped together for this iteration of the calculation.
The script will be ran quarterly.
Incomplete objects will not be
listed for now, like sugar’s without lids, butter dishes lid only etc.
Auctions won with mixed sets are not counted. It is unreasonable to resolve the price per unit if butter dishes are sold with bread and butter plates.
Auctions won with mixed sets are not counted. It is unreasonable to resolve the price per unit if butter dishes are sold with bread and butter plates.
A salt and pepper shaker auction counts as a lot of 2 since people often sell them seperately.
There were 193 won auctions in the last three months used for this iteration.
Since this particular pattern goes by multiple names, we performed two searches: one for sharon rose and one for cabbage rose. We combined the results and removed the duplications.
For Transparency, the compiled excel sheet is posted here.
Price Values
for won auctions 12-15-12 through 3-15-13
*Published Data is from Schroy, Ellen T. Warman's Depression Glass. Iola, WI: krause publications, 1997.
**cream soups and flat soups are unfortunately combined in this iteration*** tumblers are not segregated by tumbler size, shape, or thickness.
Discussion
The
standard deviations are very high. We did not take into account
quality. This has to do with the (1) small sample sizes, (2) the
omission of shipping, and (3) the effect of batch sales.The small sample sizes will be remedied as the study expands over time. There will be moving data points and global averages as we get more data points next quarter.
The shipping may be included in the next study, being added to the sold price and divided with the batch prices so that the price per unit will increase appropriately. Standard deviation may also decrease
In general, the prices in general have decreased for these items, a -$0.83 overall. The published data woefully overestimates the price on average by 283%.
Conclusion
If you would like
this study to expand to your pattern, let me know and we can work
together to perform this arduous calculation. I need a list of all the
pieces in your pattern and some pointers to tell which ones are fakes.
This may be easier with time as we automate more of the process, but for
now, it takes some time.Let me know in the comments if you used this data for anything!