Topic
Data
What the published distributions say, and how far self-reported figures drift from them.
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The girth data
Veale 2015 reports flaccid and erect girth with a tighter spread than length; here are the figures, the sample they come from and what the tighter SD implies.
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The condom-fit literature
Studies run to size condoms measure erect girth and length self-reported at home, with a fitted product as the reward; they are a separate dataset from the clinical pool.
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What the top percentile means in centimetres
Under the normal assumption the 99th percentile sits about 2.33 SD above the mean; the Veale figures show how far that is and how few claims survive it.
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Standard deviation
The SD is the typical distance from the mean, and it is the second number you need before a mean tells you anything about where a figure sits.
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Citing the paper
The reference is Veale, Miles, Bramley, Muir and Hodsoll, BJU International 2015; here is how to cite it and which figures to attribute to it.
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Flaccid spread
Across the pooled studies, flaccid length has the largest relative standard deviation of any state, which is the data-side echo of how much it wanders.
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Shoe size
The shoe-size belief has been tested directly and found no useful relationship; here is what was measured, and why the belief survives anyway.
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Two calculators, two answers
Online percentile calculators differ because they draw on different studies, different states and sometimes self-report; the disagreement is in the inputs, not the arithmetic.
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One method change, one shifted mean
Switching a protocol from non-bone-pressed to bone-pressed, or from stretched to erect, moves an entire study's mean by an amount that dwarfs its confidence interval.
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Ethnicity
Veale 2015 looked for ethnic differences and concluded the pooled data could not support claims either way; that absence of evidence is the honest finding.
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Three states, three averages
A single table of the Veale means and SDs by state, so the three figures that get confused for each other sit next to each other with their spreads.
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CI or SD
A confidence interval bounds the mean; a standard deviation describes the individuals. Papers report both and readers routinely swap them.
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Fewer erect measurements
Far fewer men in the pooled data were measured erect than flaccid or stretched, which is why the erect figures carry wider uncertainty.
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Reading a girth percentile
Because girth has a smaller standard deviation than length, a few millimetres of girth error move a percentile further than the same error in length would.
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The studies have error bars too
Clinician measurement is better than self-measurement, not perfect; test-retest figures where reported set a floor under the precision of any pooled number.
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Which studies get published
Studies with striking findings are likelier to be published and cited; in this literature that favours unusual populations and surprising means.
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Height
Studies that looked for a link between height and length report at most a weak positive correlation - real in a large sample, useless for predicting any one person.
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The chart in the article
Percentile charts in magazine features are usually redrawn from a single study or a self-report survey without saying which; a reader should ask.
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Exclusion criteria
Measured studies exclude men with conditions that affect the measurement, which is correct for their purpose and also trims the tails of the reported distribution.
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When two clinicians measure
Studies that had two observers measure the same men report good but not perfect agreement, which is the floor of uncertainty in even the best data.
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Percentile of what
A percentile is only meaningful relative to a named sample; the same figure is a different percentile against a clinic sample, a self-report survey or a single country.
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The nomogram figures
Veale 2015 published nomograms for flaccid, stretched and erect length and for girth; each is a mean and a spread drawn as a curve, nothing more.
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The column after the mean
Every measured mean in a paper comes with an SD, SE or CI in the next column, and which one it is changes what the number means.
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Stretched length across papers
Stretched length depends on how hard the measurer pulls, and no two protocols standardise that identically, so it varies between studies more than erect length does.
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How rare the extremes are
Under a normal curve, each additional standard deviation from the mean cuts the remaining share sharply; the extremes people talk about are rarer than the talk implies.
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Two percentiles, one person
Length and girth are only moderately correlated, so most men sit at different percentiles on the two; the same percentile on both is the exception.
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What the authors say to be careful about
The paper's own limitations section names heterogeneity, clinic-based samples, uneven erect data and unverifiable ethnicity; a reader should carry them along with the means.
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Nomogram
A nomogram is a chart that lets you read one quantity from another without arithmetic; here it maps a measurement to a percentile.
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When the reward depends on the number
Some self-measured studies gave participants a product sized to their reported figure; that design changes who takes part and how carefully they measure.
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Why the papers use centimetres
Clinical studies report in centimetres to one decimal; inch figures in circulation are conversions, and every conversion is a chance for a rounding slip.
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The average people carry in their heads
Ask people what average is and they name a figure above what clinicians measure; self-report, media selection and viewing angle each push perception the same way.
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How Kinsey collected size data
Kinsey's figures were self-measured by participants and mailed back on cards, which makes them the founding example of the self-report problem.
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Designing the honest comparison
The clean test of self-report inflation is the same men measured both ways under one protocol; here is what that design needs and what has come close.
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Which average did you mean
Flaccid, stretched and erect, bone-pressed or not, clinician-measured or self-reported - each has its own average, and the word alone names none of them.
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The 2D:4D literature
A handful of studies report a relationship between the second-to-fourth finger ratio and stretched length; it is a research curiosity, not a predictor.
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One and two standard deviations
Under a normal curve about two-thirds of a sample lie within one SD of the mean and about 95 percent within two; applied to Veale, that gives real ranges.
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The world map of averages
The country-by-country averages that circulate online mix self-reported surveys with clinical studies of different methods, then rank them to one decimal place.
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One decimal in the table
A published mean is rounded to match its uncertainty, which is right for the data and wrong to treat as exact; the rounding is a statement about precision.
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Heterogeneity
When the studies in a pool differ more than chance allows, the pooled mean is an average of different things; Veale 2015 reports this and it should be read.
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Percentiles
A percentile is the share of the reference sample that measured below a figure; the 50th is the median, the 90th means nine in ten measured less.
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Who volunteers
Men who agree to be measured for a study are not a random draw, and the direction of that selection is a standing caveat on every reported mean.
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Why self-reported figures run high
The gap between what people report and what gets measured is consistent, well documented, and mostly not dishonesty. Method explains more of it than motive.
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The paper that made stretched length a proxy
A small 1996 study measured men flaccid, stretched and erect and found stretched length tracked erect; that finding is why clinics take stretched length today.
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How a size study is built
Recruitment, exclusion, measurer, instrument, state and reporting: each design choice moves the reported figure, and knowing them is how you read any study.
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Reading a nomogram without fooling yourself
What a percentile is, how a nomogram is built from a mean and a standard deviation, and how to place a measured figure on it with its uncertainty attached.
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The Veale meta-analysis, read properly
The paper the whole subject rests on: what it set out to do, what it pooled, what it reports, and where its own authors say to be careful.
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What the published data actually says
One large meta-analysis, measurements taken by health professionals rather than self-reported. The numbers are lower and the distribution is narrower than almost anyone expects.