Penis Percentile Calculator

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This is more of an opinion page, and as such the tone may be slightly different than the rest of the pages in this site.

You might believe that this website is wrong and that there's no way the average size is around 5.5", as it is clearly 7"-8". Right? Well...

Even if everyone around you says they're [insert number here] inches big, it's probable that they're either exaggerating a bit too much or outright lying. They might not even be trying to exaggerate, but they can end up doing so by not measuring themselves properly, rounding up too much or being fooled by other's perceptions (the commonly referred "girl inches" vs "real inches"). Secondly, unless someone took out a ruler or other measurement device and measured their partner, it's likely for them to believe whatever size their partner says they are, further spreading the myth due to a lack of verifiability.

Same thing goes for porn: using camera tricks and shorter actors and actresses, they can make a smaller size seem bigger than it actually is. Many things common in that industry are flat out wrong in real life. If not enough information is provided about an environment, the brain can make some crazy assumptions. This video from Vsauce on YouTube talks about a similar yet unrelated effect, the "Moon Terminator Illusion" where people perceive distance wrongly without the right context in front of them. Skip to 2:17 if you want to go straight to the point (and watch until 4:19). Also, have a look at this (safe for work) image gallery with three paper rolls in sizes 7"x5", 7.5"x5.5" and 8"x6" (already huge!) compared to nearby objects. It's very easy to make them appear larger just by using clever angles.

Perspective can truly be deceiving. You normally view yourself from a top-down point of view, with other elongated parts of your body nearby (due to foreshortening) as the only way to compare. Anyone else is going to see it across from them, not foreshortened and with enough "clues" about the environment. You can try comparing yourself to other objects to have a better understanding of its real size, or make a paper roll roughtly its size and compare it that way.

This page made by someone else has more details on the matter: Unraveling Size (NSFW)

But there are valid concerns...

There is cause to be concerned that almost all of these studies sample men who must consent to be measured (or even worse men who must volunteer to be measured). This raises the issue of volunteer bias since we would expect that men who are more insecure about their size would be more likely to be smaller and more likely to not agree to be measured. In the studies where men were randomly selected by the researchers, this wouldn't be too much of an issue except that most of those studies tend to have an appreciable portion of the initial random sample refuse to be in the study, potentially biasing the sample towards larger sizes. Contrarily, many studies sample men in urology clinics where there are ample biases for smaller sizes due to high rates of ED, small penis concerns, genital disorders, etc. Which is why rare studies like Ponchietti et al. 2001 which utilize completely random sampling are useful to asses these potential issues.

Other common beliefs are that microsized members lower the average significantly, and that these datasets compare people from ethnicities where the average is smaller. Of course, you'd need to read each and every study here to confirm this for each one, but for the most part, they sample people who are expected to be representative of the general population. The concerns about differences between geographies/ethnicities may have some justification, hence the Western Average and Eastern Average. However, there is currently no definitive evidence proving or disproving genuine differences in the distributions of sizes between populations around the world. This is because a number of possible confounding factors can lead to differing results in studies (differences in: measuring technique, volunteer biases & other sampling biases, exaggeration biases, etc. can make two studies even within the same country have wildly different results). For instance, common social preconceptions in some regions typically put African men under more pressure to have larger sizes and put Asian men under less pressure to be bigger due to assumptive racial stereotypes. Even if both populations had identical size distributions, these cultural differences in size expectations could cause unequal volunteer biases leading to higher averages for African men and lower averages for Asian men despite having no genuine size difference between the populations. Such confounding factors make it impossible to prove that the apparent population difference seen between the Western and Eastern averages is definitively due to a difference between the sizes of each population. Proving whether or not a genuine size difference is found between different subpopulations would require properly controlling for all other possible confounding variables, such as by having a single researcher measure each group the same way with nonvoluntary random sampling.

Additionally, there is suspicion that some of the difference in length seen in Asian geographies is due to poorly described methods in which Non Bone-Pressed studies incorrectly describe themselves using Bone-Pressed terminology. Yet, a higher rate of NBP/BP misclassification alone doesn't fully explain the differences observed, so while it is possible that there is a difference in the sizes between the two populations, it is not certain. Furthermore, any geographical/racial size differences are expected to be at most tenths of an inch so as to be relatively inconsequential to the individual, and imperfect studies show racial groups from the same geography usually fall into a similar range. If you're still unsure about these averages, you can see for yourself the differences in the Dataset List page. It documents the average for the studies used in calcSD and other information about them, such as the countries they gathered data from.

We get quite a few people theorizing that the erect dimensions reported are lower than in reality because of researchers measuring subjects who do not have a complete erection. However, when comparing regular studies to studies that utilize drug-induced erections to ensure the erection is at 100% while measuring, I see no evidence that the drug-induced erect dimensions are proportionally larger than the other dimensions, which suggests that the studies without drug-induced erections have no difference in erection quality.

There are other claims that the distributions of length and girth are not normal since "there can't be less than zero length or girth", but that's not really relevant as the theoretical ~1 in a billion who would have been negative or even close to zero under the normal approximation is instead a nonzero very small size, which has very little effect on the potential for error. But, when investigating the normalcy of the distributions, almost always the log-normal distribution (which is essentially the mathematical equivalent of the normal distribution, but with lower bound at zero instead of negative infinity) over-skews the distribution to the right, resulting in rarities that usually give a worse fit to the study data (min/max, median, & percentiles) than the normal distribution. Similarly some claim "there's more people on one side of the average than the other, the distribution is skewed." There's been plenty of studies and some show right-skew while others show left-skew, which suggests that if there is skew, it would be very minor at most, additionally the actual data distributions are about as close to normal as can be expected (especially given the potential sampling biases and relatively small sample sizes), and Ponchietti et al. 2001 which finds minor left skew while not having a volunteer biased sample.

Some also claim that "most people on the high side of the average are more sexually active, therefore women encounter larger sizes more." There's currently not much evidence proving or disproving this claim, so... you can believe what you like, but there's little evidence of this causing much of a difference in the dating pool (and it doesn't apply to the actual distribution of sizes among men in general). Furthermore, there is some evidence that women's current partners are more likely to be somewhat larger than average (the distribution of sizes of current partners is a byproduct of average time spent dating partners of each size). This suggests that even if larger sizes at first over-represent themselves in the dating pool, they may also be disproportionately removed from the dating pool for longer times by partners who are more likely to be dating them than smaller sizes. Which would suggest that women may not be more likely to randomly encounter these larger sizes in the dating pool. Another contributing factor could be that instead of larger sizes being more active, smaller sizes under-represent themselves in the dating pool due to insecurity, leading the current partners average to shift slightly larger.

We should also point out that these researcher measured studies result in an honest distribution of sizes. They are not trying to measure the biggest possible - furthest pressed into the bone - maximized dimensions, so realistically you will over-estimate your percentile relative to other people if you don't use honest measurements.

Lastly, note that there is inherent disagreement between these studies, which we attempt to show in the chart page, this disagreement is the result of a combination of differences in various biases due to heavy reliance on volunteer samples, potential differences between populations sampled, and different biases in the methods and measuring techniques used by the researchers. As such, you could estimate that there is an uncertainty in the averages of our datasets which may be at most ±0.2".