The standard statistical approach to risk management is based on a “bell curve” or normal distribution, in which most results are in the middle and extremes are rare.
在统计学中，风险管理的标准方法是基于“钟形曲线”（或曰正态分布）的，绝大多数结果分布在中间，极端情况十分罕见。
The standard pattern distribution of normal population: Most (74.5%, 82/110) of the unrelated healthy individuals displayed such a pattern without any translocation, hybridization and mosaicism.
正常人的标准带型分布：在检测的110名正常人中，74.5％（82／110）为标准带型，无易位、杂合、体细胞嵌合等情况。
Statistics histogram data processing scheme is designed. Standard deviation of frequency modulation is found out according to normal distribution characteristics.
设计了统计直方图数据处理方案，按照正态分布的特性找出了寄生频率调制的标准偏差。
The normal mixed distribution model can be used to get probability density or to simulate population which can not be fitted by standard parameters distribution classes.
正态混合模型还可以用来对那些不能用标准的参数分布族来拟和的总体进行密度估计或近似。
The table of standard normal distribution was handled correctly by use of Raphson numerical integral, by this way, the optimum design was connected with reliability design organically.
文中提出采用辛卜生数值积分较好地处理了正态分布数值表，从而将优化设计与可靠性设计有机地结合起来。
RANDN (n) is an N-by-N matrix with random entries, chosen from a normal distribution with mean zero, variance one and standard deviation one.
是一个n - n矩阵随机作品，选自正态分布均值为零，方差一个标准偏差为一。
If it is a normal distribution, standard deviation (s) is observed.
若是正态分布，则进一步观察标准差。
The distribution form of safety factor is standard normal distribution while soil parameter distribution is normal or lognormal distribution.
土性参数的分布形式取正态分布或者对数正态分布时，安全系数的分布均呈标准正态分布；
The models were estimated via Gibbs sampler with data augmentation by a mixture of standard exponential distribution and standard normal distribution to represent the asymmetric Laplace distribution.
由于模型参数的后验条件分布没有确定的分布形式，通过数据扩充得到参数的完全条件分布从而实现模型参数的贝叶斯估计。
The models were estimated via Gibbs sampler with data augmentation by a mixture of standard exponential distribution and standard normal distribution to represent the asymmetric Laplace distribution.
由于模型参数的后验条件分布没有确定的分布形式，通过数据扩充得到参数的完全条件分布从而实现模型参数的贝叶斯估计。
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