You can find regulations about clothing sizes in the EN 13402 standard, and a series of physical measurements in the SIRI-dataset.
Reading the standard, I see that t-shirt sizes (men), for example, are mainly based on chest circumferences. Size 'M' is suitable for chest circumferences between 94 and 102 cm. Size S is 8 cm smaller, size L is 8 cm bigger, XL is 16 cm bigger and XS is 16 cm smaller than size M.
When I calculate the median and standard deviation of all the chest circumferences (adult males) I find in the SIRI-dataset, I find a median of 99.6 cm, and - surprise - a standard deviation of 8.4 cm. So, I tend to believe that clothing sizes follow, in some way, the normal distribution.
Size M refers to the median size, and the intervals between the size codes have about the same value as the standard deviation. So, size S is one standard deviation smaller than size M, and XL is two standard deviations bigger than size M.
If haven't checked other types of clothes and other physical sizes, so I cannot guarantee that my conclusion is correct for any type of garment.
The standard normal distribution is a special case of the normal distribution. The standard normal has mean 0 and variance 1.
The domain of the normal distribution is infinite.
It means distribution is flater then [than] a normal distribution and if kurtosis is positive[,] then it means that distribution is sharper then [than] a normal distribution. Normal (bell shape) distribution has zero kurtosis.
No. Normal distribution is a special case of distribution.
The normal distribution can have any real number as mean and any positive number as variance. The mean of the standard normal distribution is 0 and its variance is 1.
The standard normal distribution is a normal distribution with mean 0 and variance 1.
The standard normal distribution is a special case of the normal distribution. The standard normal has mean 0 and variance 1.
le standard normal distribution is a normal distribution who has mean 0 and variance 1
When its probability distribution the standard normal distribution.
No, the normal distribution is strictly unimodal.
The domain of the normal distribution is infinite.
Yes. When we refer to the normal distribution, we are referring to a probability distribution. When we specify the equation of a continuous distribution, such as the normal distribution, we refer to the equation as a probability density function.
The standard normal distribution has a mean of 0 and a standard deviation of 1.
The Normal distribution is, by definition, symmetric. There is no other kind of Normal distribution, so the adjective is not used.
Yes, but it converges to the Gaussian (Normal) dirstribution for large sample sizes.
The normal distribution would be a standard normal distribution if it had a mean of 0 and standard deviation of 1.
Children's clothing sizes are divided into separate categories for specific age groups.