这方面尤其如此，因为贵国那个地区的不同地方差别很大。
This is especially so, since there are such vast differences between the various places in that part of your country.
图3：方差区间内完成任务的可能性。
Figure 3: Likelihood of completing a task within the variance interval.
非常量误差方差或异方差性。
由模型说明的方差比例范围为21%至28%。
The proportions of the variance explained by the models ranged from 21% to 28%.
应该用控制循环来管理项目，促使项目方差为零。
Projects should be governed using a control loop to drive project variance to zero.Figure 8: project governance control loop.
应用正交设计实验方法和方差分析。
Methods: Orthogonal design and analysis of variance were used.
数据分析采用方差分析、多元回归分析。
Data were analyzed using variance and multiple regression analysis.
随机变量的方差衡量随机变量值与期望值偏离的程度。
The variance of a random variable measures how far from the expected value its values typically are.
去除的风险测量，即，减少关键项目度量标准的方差。
A measure of risk removed, i.e., the reduction of variance of key project metrics.
统计学分析计量资料差异性测定采用方差分析。
Statistics analysis: The difference of measurement data was detected by analysis of variance.
注意到风险的严重程度直接关系到项目参数的估计中的方差。
Note that severity of risk is directly related to the variance in the estimation of a project's parameters.
使用组合方法获得了稳定的结果和较大的方差减缩。
Stable results and high variance reduction using the compound method have been obtained.
注意选择度量标准的指导原则是它们怎样影响具体项目参数的方差。
Note that a guiding principle for choosing metrics is how they will affect a specific project parameter's variance.
因此，由于在新知识的获取方面进行合作交流，方差随着时间减少了。
Hence, the variance diminishes over time due to collaborative interaction on new knowledge acquisition.
假设估算的任务持续时间是3个月，并且估计的方差是1 个月。
Suppose the estimated duration of a task is 3 months, and the variance of the estimate is 1 month.
很明显，随着项目参数估计中方差的增加，成功完成项目的可能性就减少。
Clearly, as the variance in the estimates of project parameters increases, the likelihood of completing the project successfully decreases.
我们全球性的优势源于在保持一致的同时也乐于接受地方差异。
Our global strength comes from celebrating local differences whilst understanding that some things should be kept the same.
这个简单线性回归过程中的下一步是确定其余的预测方差是否可以接受。
The next step in the simple linear regression procedure is to determine if the remaining squared error of prediction is acceptable or not.
您可以利用此函数将您的样本方差计算转换为样本标准差计算，如清单8所示。
You can use it to turn your variance measurement into a standard deviation measurement, as shown in Listing 8.
例如，与项目成本或持续时间无关的度量标准不能帮助评估迭代中的方差削减。
For example, a metric that does not correlate to the project cost or duration cannot aid in assessing the variance reduction in the iterations.
3方差的专业定义是随机变量的二次中心矩，与期望值之差的平方的加权平均值。
The technical definition of variance is the random variable's second central moment, the weighted average of the square of the differences from the expected value.
在期权定价的蒙特卡罗模拟中，重要性抽样是一种有效的方差减小技术。
Importance sampling technique is an effective variance reduction technique in Monte Carlo simulation method for pricing options.
利用协方差分析方法评价教学效率，为教学的科学管理提供了重要依据。
We use the covariance analysis method to appraise teaching efficiency and provide an important basis for scientific management of teaching.
该方法基于一个隐含的假设，即可以肯定地做出计划：也就是，持续时间的方差非常低。
It is based on the implicit assumption that the plan can be made with certainty: i.e., that the variance of the durations is very low.
尽管全球化趋势不断加强，地方差异性依然主宰着大型零售业，Terry说。
Despite globalisation, local differences still hold sway over mass retailing, says Sir Terry.
因为这时模型协方差阵结构仍含有方差参数，因此我们的目标是寻求可行估计。
The variance-covariance matrix still include parameter of variance in this condition, so our purpose is to look for feasible estimations.
要想将上面所讨论的所有内容都成为可实行的，团队必须找到一个计算项目参数方差的方法。
For all of the above discussion to be practical, the team must find a way to compute the variance of the project parameters.
最大类间方差法是一种常用而有效的图像分割算法，并已在许多实时场合中采用。
The Otsu's method is an effective algorithm for image segmentation, and has been widely employed in various real-time applications.
线性无偏最小方差估计与最优加权最小二乘估计是线性模型下两种最常用的估计方法。
The linear unbiased minimum variance estimate and the optimally weighted least squares estimate are two of the most popular estimation methods for a linear model.
线性无偏最小方差估计与最优加权最小二乘估计是线性模型下两种最常用的估计方法。
The linear unbiased minimum variance estimate and the optimally weighted least squares estimate are two of the most popular estimation methods for a linear model.
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