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Eccentricity (also called quirkiness) is an unusual or odd behavior on the part of an individual. This behavior would typically be perceived as unusual or unnecessary, without being demonstrably maladaptive .
In mathematics, the eccentricity of a conic section is a non-negative real number that uniquely characterizes its shape. One can think of the eccentricity as a measure of how much a conic section deviates from being circular. In particular: The eccentricity of a circle is 0. The eccentricity of an ellipse which is not a circle is between 0 and 1.
Eccentricity is contrasted with normal behavior, the nearly universal means by which individuals in society solve given problems and pursue certain priorities in everyday life. People who consistently display benignly eccentric behavior are labeled as "eccentrics".
The simplest case of a normal distribution is known as the standard normal distribution or unit normal distribution. This is a special case when μ = 0 {\textstyle \mu =0} and σ 2 = 1 {\textstyle \sigma ^{2}=1} , and it is described by this probability density function (or density): φ ( z ) = e − z 2 2 2 π . {\displaystyle \varphi (z ...
A graphical tool for assessing normality is the normal probability plot, a quantile-quantile plot (QQ plot) of the standardized data against the standard normal distribution. Here the correlation between the sample data and normal quantiles (a measure of the goodness of fit) measures how well the data are modeled by a normal distribution. For ...
To assess whether normality has been achieved after transformation, any of the standard normality tests may be used. A graphical approach is usually more informative than a formal statistical test and hence a normal quantile plot is commonly used to assess the fit of a data set to a normal population.
It should only contain pages that are Normality tests or lists of Normality tests, as well as subcategories containing those things (themselves set categories). Topics about Normality tests in general should be placed in relevant topic categories .
The Shapiro–Wilk test tests the null hypothesis that a sample x 1, ..., x n came from a normally distributed population. The test statistic is = (= ()) = (¯), where with parentheses enclosing the subscript index i is the ith order statistic, i.e., the ith-smallest number in the sample (not to be confused with ).