## Posts filled under #meencantan

Mandaloriano :D Diganle a mi @gaztana que dibuja bien -_- que es media boba y no me cree 3000 mg para que sea dibujante oficial de Deathwolftroopers :D Aunque para mi ya lo es #starwars #mandaloriano #blobliblu #meencantan

## An extract on #meencantan

Two statistical models are nested if the first model can be transformed into the second model by imposing constraints on the parameters of the first model. For example, the set of all Gaussian distributions has, nested within it, the set of zero-mean Gaussian distributions: we constrain the mean in the set of all Gaussian distributions to get the zero-mean distributions. In that example, the first model has a higher dimension than the second model (the zero-mean model has dimension 1). Such is usually, but not always, the case. As a different example, the set of positive-mean Gaussian distributions, which has dimension 2, is nested within the set of all Gaussian distributions.

a measure of location, or central tendency, such as the arithmetic mean a measure of statistical dispersion like the standard deviation a measure of the shape of the distribution like skewness or kurtosis if more than one variable is measured, a measure of statistical dependence such as a correlation coefficient A common collection of order statistics used as summary statistics are the five-number summary, sometimes extended to a seven-number summary, and the associated box plot. Entries in an analysis of variance table can also be regarded as summary statistics.

Logan gives the following example. Furness and Bryant measured the resting metabolic rate for 8 male and 6 female breeding Northern fulmars. The table shows the furness data set. The graph shows the metabolic rate for males and females. By visual inspection, it appears that the variability of the metabolic rate is greater for males than for females. The sample standard deviation of the metabolic rate for the female fulmars is calculated as follows. The formula for the sample standard deviation is s = i = 1 N ( x i x ) 2 N 1 . {\displaystyle s={\sqrt {\frac {\sum _{i=1}^{N}(x_{i}-{\overline {x}})^{2}}{N-1}}}.} where { x 1 , x 2 , , x N } {\displaystyle \scriptstyle \{x_{1},\,x_{2},\,\ldots ,\,x_{N}\}} are the observed values of the sample items, x {\displaystyle \scriptstyle {\overline {x}}} is the mean value of these observations, and N is the number of observations in the sample. In the sample standard deviation formula, for this example, the numerator is the sum of the squared deviation of each individual animal's metabolic rate from the mean metabolic rate. The table below shows the calculation of this sum of squared deviations for the female fulmars. For females, the sum of squared deviations is 886047.09, as shown in the table. The denominator in the sample standard deviation formula is N 1, where N is the number of animals. In this example, there are N = 6 females, so the denominator is 6 1 = 5. The sample standard deviation for the female fulmars is therefore s = i = 1 N ( x i x ) 2 N 1 = 886047.09 5 = 420.96. {\displaystyle s={\sqrt {\frac {\sum _{i=1}^{N}(x_{i}-{\overline {x}})^{2}}{N-1}}}={\sqrt {\frac {886047.09}{5}}}=420.96.} For the male fulmars, a similar calculation gives a sample standard deviation of 894.37, approximately twice as large as the standard deviation for the females. The graph shows the metabolic rate data, the means (red dots), and the standard deviations (red lines) for females and males. Use of the sample standard deviation implies that these 14 fulmars are a sample from a larger population of fulmars. If these 14 fulmars comprised the entire population (perhaps the last 14 surviving fulmars), then instead of the sample standard deviation, the calculation would use the population standard deviation. In the population standard deviation formula, the denominator is N instead of N-1. It is rare that measurements can be taken for an entire population, so, by default, statistical software packages calculate the sample standard deviation. Similarly, journal articles report the sample standard deviation unless otherwise specified.