The (statistical) Truth About Cock Size

I randomly chose 50 guys from the PE data site and recorded their baseline stats into a spreadsheet and crunched the numbers:

Mean length (BPEL): 6.141 inches
Std dev length: 0.831 inches

Mean girth (EG): 5.076 inches
Std dev girth: 0.579 inches

Maximum length: 7.75 inches (1.936 std dev above the mean)
Minimum length: 3.75 inches (2.877 std dev below the mean)

Maximum girth: 6.75 inches (2.891 std dev above the mean)
Minimum girth: 2.8 inches (3.931 std dev below the mean)

Max. difference between std devs (girth vs. length): 2.445 fold
Mean difference between std devs (girth vs. length): 0.782 fold
Min. difference between std devs (girth vs. length): 0.038 fold

The person with the largest difference measured 4”x5”, while the several people with the smallest difference measured 6”x5”. So, my prediction holds (for this sample, anyway) that penises typically get girthier as they get longer and vice versa.

For the sample as a whole, I did a scatter plot and linear regression on the data, which shows a positive correlation between length and girth, i.e. as length increases, girth also increases. However, given that the correlation coefficient is only 0.217, this is a weak relationship.

The other interesting bit that I got from all of this analysis is that the numbers for Thunder’s Place are very similar to the LifeStyles data set.

TP mean length: 6.141 +/- 0.831 inches
LS mean length: 5.877 +/- 0.825 inches

TP mean girth: 5.076 +/- 0.579 inches
LS mean girth: 4.972 +/- 0.508 inches

I suspect that the higher mean length for Thunder’s guys is due to us ‘trying harder’ when we take our bone press measurements. We might accept a little pain when we press, unlike the participants in Cancun.

I recall seeing other girth-length correlations (I think using larger datasets?) with a stronger r. Wish I could remember where the analyses were on this site. Every time I’ve seen someone do this analysis, in any case, there has been a reliable positive correlation (unsurprisingly).

Yeah, I’ve always noted, when guys ask about average size, that we PEers probably add on an additional .25-.5” beyond what doctors get with a BP at 100% erection via our various tricks (e.g., pushing our hips out, pushing the erection down to parallel to the ground, etc.). There may also be a bit of self-report exaggeration in the TP data. The Cancun Lifestyles study found the greatest average length out of all the third-party studies that have been done (probably due to self-selection), so the real average is probably a little lower.

How can I figure out my standard deviations ranks? Bpel 7.5 (pushing hard) eg 6

I found a correlation between length and girth back in 2006. Here is a post of mine from back then about it:

“I looked at the first 612 posters’ earliest stats listed in ThunderPlace’s PE Data Site (link located at bottom of page). I stopped at that point since this is as much time as I could put into it at the moment.

————————-<4 G—-4-4.49 G—-4.5-4.99 G—-5-5.49 G—-5.5-5.99 G—-6-6.49 G—-6.5-6.99 G—-7> G

4-4.99 BPEL———-10%—-50%————25%————5%————-10%————0%————0%————-0%
20 posters————-2 ——-10—————5—————-1—————-2—————-0—————0—————-0

5-5.99 BPEL———-4%——17%————47%————26%————-3%————1%————0%————-1/2%
156 posters———-6———27—————74—————41—————-5—————2—————0—————-1

6-6.99 BPEL———-0%——-7%————34%————42%————-13%———-3%————1/3%———-1/3%
268 posters———-0———-18————-91—————113—————35————-9—————1—————-1

7-7.99 BPEL———-0%——-3/4%———12%————33%————-30%———-18%———-5%————-3/4%
132 posters———-0————1————-16—————44—————-39————-24————-7—————-1

8-8.99 BPEL———-0%———0%————0%————17%————-34%———-34%———-10%————-3%
29 posters————0————0—————0—————-5—————-10————-10————-3——————1

9> BPEL—————-0%———0%————0%————-0%————-57%———-14%———-14%————-14%
7 posters—————0————0—————0—————-0—————-4—————1—————1——————1

What follows below is just an estimate, as I merely made marks in the above chart when a length and girth were in a range, and didn’t record precise numbers, which would have taken far more time. For instance, if someone had a 6.375 BPEL and 5.1 Girth, I made one mark in the 6-6.99 BPEL and 5-5.49 Girth row/column intersection.

To get an idea of estimated average correlations, I’m assigning the following (once again, this is not precise but should give a reasonable picture as to the average girth relation differences between the length ranges). It’s clear in the above chart that a correlation exists, but perhaps the following will help clarify it.

<4 G range is assigned an overall 3.75 G estimate
4-4.49 G range is assigned an overall 4.25 G estimate
4.5 -4.99 G range is assigned an overall 4.75 G estimate
5-5.49 G range is assigned an overall 5.25 G estimate
5.5-5.99 G range is assigned an overall 5.75 G estimate
6-6.49 G range is assigned an overall 6.25 G estimate
6.5-6.99 G range is assigned an overall 6.75 G estimate
7> G range is assigned an overall 7.25 G estimate.

From the above assigned girth estimates the following result is arrived at:

BPEL —————-Averaged Girth
4-4.99”———————-4.5”
5-5.99”———————-4.8”
6-6.99”———————-5.1”
7-7.99”———————-5.6”
8-8.99————————6.0”
9>”—————————-6.2”

Using the LifeStyles means and std dev:

Length:
7.5 - 5.877 = 1.623 inches
1.623 / 0.825 = 1.967 standard deviations above the mean, which is the 97.54 percentile or 1 in 41.

Girth:
6 - 4.972 = 1.028 inches
1.028 / 0.508 = 2.024 standard deviations above the mean, which is the 97.85 percentile or 1 in 47.

Yeah, that is why I stopped at a sample size of 50 individuals :)

From my analysis this afternoon, the slope of the line for the linear regression was y=0.3242x + 3.085. When arbitrary length numbers are plugged into this equation the girth numbers look like this:

BPEL …… Expected girth

4” …………… 4.38”
5” …………… 4.71”
6” …………… 5.03”
7” …………… 5.35”
8” …………… 5.68”
9” …………… 6.00”

So your estimates are really very good.

Yeah but you goota know how to use it first!

The only thing that puzzles me, about the girth, is if you look at self reported surveys, there are always many more people below 4.5 than you are suggesting from the lifestyles data.

Definitive penis size survey:
20th percentile - 4.3”
30th percentile - 4.7”

from your calculations :
15.9th percentile - 4.5”

just seems strange that self reported studies would have more people LOWER, since inevitably it should be higher from self-measuring bias and inflated stats.

especially when you look at this

your stats:
5.48 = 84th percentile

from definitive penis size survey
5.5 = 70th percentile

which proves that the data is inflated. The only thing that I can think of is that the girth data from lifestyles is not even close to normally distributed and that there are many more people below 4.5” than your calculations are suggesting.

Priapologist,

I’m a bit surprised you went with just 50 when more was available. Just not a very solid amount to work with.

I, and others, have already covered all of these points in this thread, but here they are again:

1) The LifeStyles data are probably skewed upward due to self-selection bias, just as the Thunder’s data are probably skewed upward due to self-selection bias.

2) I would not trust the results of the Definitive Penis Size Survey any farther than - well, you get the idea.

3) I stated emphatically that the girth data were not normally distributed, and that I was analyzing it only because people wanted to have a general idea.

4) These are statistics, not the Word of God writ large upon stone tablets.

You are joking… right?

No. I realise 50 can work, but more would likely produce more stable results. I’m not suggesting going all the way up to 612 like I did. At least a 100, no?
I didn’t say it’s not solid, I said it’s not very solid (exact). :)

Priapologist,

Of course it does appear rather silly of me to nit-pick the amount of data you used when the result mirrors mine (if range is taken into account in your data) of 612. It’s extremely close, almost an exact match.

Thanks a lot Priapologist.

To more accurately track my percentile growth, how can I convert standard deviation to percentile? I tried looking it up, but I don’t understand. They say I need a z table?

redskins2k9,

Here’s a table for you:

If you are, say, 0.49 standard deviations above the mean, then you look in the row for 0.4 and the column for 0.09, and you find that 0.6879 (i.e., 68.79%) of the total population is below you for that variable.