Walking Dead #1 Black Label vs White Label - an Answer! UPDATED 2/4/14

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Balham, I love it when people use "knob" as a put down. Seriously. It's not used enough in the States.

Knob is a great word to use in these circs. So is "tit" (as in "you absolute tit").

Both have the advantage of not being spooned out, as well.

Wow. I think this thread may have a first for the CGC boards (or any board for that matter): two boardies apologizing! I never see that. Huzzah to the both of you for being gentlemen.

Hey Guys,

It has been a while since I have had a raw or graded Walking Dead 1 in my comic shop. I have obviously heard white vs black covers forever, but I honestly am not sure what the difference looks like.

I see you guys posting pics of your 1's and discussing white vs black, but can someone post an image of a white & a black side by side in the same post and/or describe which part of the cover we are looking at to tell the difference between them?

I just picked up a 1 in my store recently and plan on slabbing it, but didn't really examine it closely to see if it is a white or black cover, just for condition.

Thanks for the help.

Mark Hay

Splash Page Comic Art & Comic Asylum

Also, @ dragonmanagement & ComicsNYC22

Sure Mark. The difference is in the "Mature Readers" warning below the issue number and price. Here is a pic, courtesy of Maloney's WDFAQ:

I'm for team black and team white!

Nice, thanks!

I'm for team black and team white!

 

GIMMIE!!!!!

please?

Thanks guys. Mine is a white label

Guess I need to throw it back in the sea and try to pull up a black label one

Mark Hay

Splash Page Comic Art & Comic Asylum

This whole discussion reminds me of that old Star Trek (TOS) episode where the last two guys of a race were fighting each other to the death....each with half their face white and the other half black, both with the white and black sides on opposite sides from ach other. The moral of that story seems equally appropriate here .

Classic stuff!

Don't worry Mark, you will have no trouble selling your white label for any more or less than you would if it were black.

-J.

Let me try and explain my comment, as I don't think it was understood:

 

Slym posted that he "didn't trust" the extrapolation, or any conclusion based on what he thought was a small sample size. You followed up with what I thought was a patronising comment telling him to admit he was going on a gut feeling, which is exactly what I thought he had already done (he wasn't saying that the stats were objectively wrong, just that he didn't trust them). That is why I said you were being a bit of a knob.

 

Anyway, on reflection, it was a bit of an uncalled for comment from me - so I apologise.

The comment was patronizing, snarky (whatever you want to call it) because saying that you don't trust the stats (or didn't trust the "extrapolation" from the sample to the population) is the same thing as saying you don't believe in the basic premise of what an entire field of study is built upon, a field that is pervasive in every area of policy, business, and high level decision making in Western society. To say that you don't trust the extrapolation is to render judgement on the veracity of the conclusions that stats, as a field, can make, which is, in my opinion, really silly, thus deserving of some snarkiness. The latitude to disagree with the numbers is built into the stats bffnut provided: the confidence interval. It was an ill informed, however well intentioned, opinion that was based on anecdotal evidence, but my annoyance stemmed from the unwillingness to change the opinion based on.....

AWW F IT. Here's a picture of a cute puppy.

Well, I can't say I agree it's the same thing.

Anyway, surely we were done with this part of the discussion a couple of hours ago when I apologised for calling you a knob...?

AWW F IT. Here's a picture of a cute puppy.

 

To be honest I disapprove of your use of a puppy as a distraction, I was under the impression the internet was only for cat pictures.

Nice!!

Well, I can't say I agree it's the same thing.

 

Anyway, surely we were done with this part of the discussion a couple of hours ago when I apologised for calling you a knob...?

I deserved being called a knob.

By the way, in case anyone missed it, bffnut has done a really wonderful job with this project. Keep up the good work!

Great Job Bffnut ..................thank for your hard work.

Hope you keep adding books.

I will James! In fact, in a few minutes.

And thanks

I scoured eBay and the registry to find more verifiable WD #1s and I was able to increase the sample size from 132 to 227. The results increased the total estimate of black labels in the population but narrowed the Confidence Interval and the margin of error.

Here are the results from the initial data:

How rare is black label Walking Dead #1?

Here is the information used to determine the answer:

 

 

Data:

white - 112

black - 20

 

 

id - grade - color

1266002 - 9.8 - white

5884001 - 9.8 - white

79182012 - 9.8 - white

113915004 - 9.8 - white

129296015 - 9.8 - white

140573002 - 9.8 - white

144970011 - 9.8 - black

146321020 - 9.8 - black

154026025 - 9.8 - white

154946001 - 9.6 - white

165995005 - 9.8 - white

167232001 - 9.8 - white

178638010 - 9.8 - white

182175002 - 9.6 - white

186798001 - 9.6 - white

191516002 - 9.6 - white

191821001 - 9.6 - black

191970001 - 9.6 - white

192488001 - 9.6 - white

193861001 - 9.4 - white

194079001 - 9.8 - white

195496001 - 9.4 - white

197225001 - 9.6 - white

197449001 - 9.6 - white

197644001 - 9.4 - white

197759001 - 9.6 - black

197855002 - 9.4 - black

198629002 - 9.4 - white

198760005 - 9.4 - black

198872001 - 9.8 - white

198923002 - 9.8 - white

199787001 - 9.4 - white

200322007 - 9.6 - white

202176002 - 9.4 - white

202875001 - 9.6 - white

203420002 - 9.8 - white

204153001 - 9.6 - white

204501001 - 9.8 - black

204895001 - 9 - white

205393001 - 9.4 - white

205791001 - 9.6 - white

206059009 - 9 - black

206222001 - 9.4 - white

206563012 - 9.6 - white

206563013 - 9.8 - white

206563015 - 9.8 - white

206563016 - 9.9 - white

207421001 - 9.8 - white

207506001 - 9.4 - white

208527001 - 9.4 - white

209169001 - 9.8 - white

209413001 - 9.6 - white

209503001 - 9.6 - white

209755001 - 8.5 - white

209755002 - 9.6 - white

209786001 - 9.4 - white

210256001 - 9.8 - white

210616001 - 9.6 - white

210873001 - 9.8 - white

211206001 - 9.6 - white

212599001 - 9.6 - white

212759001 - 9.8 - white

628194007 - 9.6 - white

709182012 - 9.8 - white

723222007 - 9.6 - white

797804003 - 9.6 - black

808607002 - 9.8 - white

905937002 - 9.8 - white

938958010 - 9.8 - black

952169001 - 9.8 - white

956195018 - 9.8 - white

957831001 - 9.6 - white

966396001 - 9.9 - black

968161006 - 9.8 - black

975877003 - 9.8 - white

975877004 - 9.6 - white

985729009 - 9.4 - white

991934004 - 9.4 - white

994664002 - 9.9 - white

1006423009 - 9 - white

1011229007 - 9.4 - white

1019293020 - 9.2 - white

1020211001 - 9.9 - white

1024487001 - 8.5 - white

1027451008 - 9.6 - black

1054779004 - 9.8 - white

1055026002 - 9.8 - white

1055107007 - 9.8 - white

1056971002 - 9.8 - white

1072637001 - 9.8 - white

1074787001 - 9.2 - white

1076175004 - 9.6 - white

1076238002 - 9.8 - white

1076401004 - 9.6 - black

1091638001 - 9 - white

1091638002 - 9 - black

1091638006 - 9.8 - white

1094188002 - 9.8 - white

1094188003 - 9.8 - black

1094428002 - 9.8 - white

1096874002 - 9.8 - black

1100551001 - 9.8 - white

1101018001 - 9.8 - white

1103146001 - 9.8 - black

1104801013 - 9.6 - white

1105049002 - 9.8 - white

1107526004 - 9.8 - white

1107956001 - 9.9 - white

1108057001 - 9.4 - white

1108376001 - 9.6 - black

1108586004 - 9.8 - white

1109516002 - 9.8 - white

1109815002 - 9.6 - white

1110547006 - 9.8 - white

1110580001 - 9.8 - white

1115011001 - 9.4 - white

1125635001 - 9.9 - white

1126235001 - 9.8 - white

1126506001 - 9.8 - black

1127144001 - 8.5 - white

1127144002 - 9.2 - white

1127646001 - 9.6 - white

1129133001 - 9.2 - white

1129425003 - 9.4 - white

1136103001 - 9.4 - white

1136174005 - 9.8 - white

1136548001 - 9.8 - white

1159072001 - 9.8 - white

1165456001 - 9.8 - white

1165603001 - 9 - white

1196966001 - 9.8 - white

1980335001 - 9.8 - white

 

 

 

Here is how I came about the answer:

 

 

To solve this problem, I had to freshen up on Binomial Distributions. This happens when data can go one of two ways, for example: yes or no, right or wrong, and in this case black or white. I used the follow two sites to re-educate myself:

 

http://www.sigmazone.com/binomial_confidence_interval.htm

http://books.google.com/books?id=m8rYUEWQx00C&pg=PA360&lpg=PA360&dq=binomial+distribution+margin+of+error&source=bl&ots=qG0eP3IPrb&sig=LbOZI4bceo6Pdoou8x9FBiIvdGQ&hl=en&sa=X&ei=SJ9_Upr2G8WqkAf6pICYDQ&ved=0CDkQ6AEwAg#v=onepage&q=binomial%20distribution%20margin%20of%20error&f=false

 

One of the things you can do with statistics is make statements about very large populations of data with a comparatively small amount of data. Businesses do this everyday when they do things like quality control. For example, instead of testing every item off of a production line, they grab random samples and test those. If they grab enough of them, they can be reasonable certain of the quality of all they items they produce.

 

So the first thing I wanted to was see if I had a large enough sample size (n). According to the text I read, you can calculate the sample size needed if you have a preliminary estimate for the proportion (p) that you are testing. This is the formula:

 

n = p (1 - p) (z / E)^2

 

where

p = proportion of interest

n = sample size

E = maximal error of estimate

z = “z value” for desired level of confidence

 

I found 132 different labels, of which 20 were black labels, so I did have an estimate: 15.15%. Using this calculation, I plugged a few numbers to see what maximal error I could have with a sample of only 132, using a desired level of confidence of 95%. Turn out it is 6.12%.

 

n = p (1 - p) (z / E)^2

n = 0.1515 (1 - 0.1515) (1.96 / .0612)

n = 131.8481

 

*z = 1.96 for 95% confidence

 

Now that I felt okay with my sample size, I needed to figure out how to calculate a confidence interval. What is a confidence interval? Well, remember that we testing a small group of data to make a reasonable estimate of the whole population of data. In statistics, this estimate is given as a range with a level of confidence. For example, "I am 95% confident that the true answer falls between 15 and 20." This is the range in which the real answer lies.

 

While not perfect, a formula used to calculate a confidence interval for binomial distributions is below. It makes a few assumptions which I will not go into (since I don't feel I can appropriately explain them), but it is a good approximation according to the text:

 

Confidence Interval =

= p +/- z (sqrt ( p (1 - p) / n ))

= 0.1515 +/- 1.96 (sqrt (0.1515 (0.8485) / 132))

= 0.1515 +/- 0.0612

 

This means that we can be 95% confident that the true proportion of black labels falls between 9.03% and 21.27%. When multiplied by the population (7266), that gives a range of 656 to 1545.

 

 

 

 

The best answer that statistics can provide is a range, with a level of confidence in that range. With the data and means available, I am 95% confident that the true proportion of black label Walking Dead #1s fall between 9.03% and 21.27% of the print run. When multiplied by the population (7266), that gives a range of 656 to 1545.

With the new data:

This means that we can be 95% confident that the true proportion of black labels falls between 13.45% and 23.55%. When multiplied by the population (7266), that gives a range of 977 to 1711.

You'll notice this narrows the range from 889 to 734, even though the band itself is higher than before.

Nice bffnut!! I'm in there somewhere.