术语“方差齐性”的详细信息

英译术语:

homoscedasticity

汉语语境:

在经典的线性回归模型中，观测值的方差齐性是一个基本的假定。在此假定下，方可进行常规的统计推断。若方差非齐而且未知，则回归分析将会遇到诸多问题。在现实生活中，人们发现异方差数据是大量存在的，所以观测值的方差齐性这种假定有时并不切合实际。若方差非齐，我们则称之为异方差。

英语语境:

In the classical linear regression model, the homoscedasticity of the data under observation is a basic assumption. Under this assumption, it can be feasible to make routine statistical inference. If the variance of observations is heterogeneous and unknown, then the regression analysis will meet many troubles. Moreover, it is found that there are many heteroscedastic data in real life. So, the assumption of the homoscedasticity is not always consistent with the reality. If the variance of observations is heterogeneous, we call it heteroscedastic data.

英译术语:

homogeneity of variance

汉语语境:

对于广义回归模型，人们也总是假设数据具有名义离差。否则，统计推断更加困难。这一假设是以观测值的方差齐性为基础的。但是，这一假设的合理性却非常值得推敲。实际上，观察数据的异方差和变离差检验是十分必要的，它是处理回归问题的重要步骤，在理论和应用上都有十分重要的意义。

英语语境:

For generalized linear and nonlinear models, it is a conventional hypothesis that observed data should have nominal dispersion; otherwise statistical inference would be more difficult. This hypothesis is theoretically based on the premise of homogeneity of variance. Nevertheless, furthur consideration is needed about the rationality of the hypothesis. Actually, testing the heteroscedasticity and varying dispersion for the data is highly necessary, which is an important step in dealing with regression problems in both theoretical and practical terms.