提出了一种能对稠油族组成与粘度进行较好关联的多元线性模型，其复相关系数为0.9885。
A new multivariate linear model was proposed to associate viscosity and group composition of heavy oil. Multiple correlation coefficient of the model is 0.9885.
本文论述多元线性回归中的回归系数与偏相关系数之间的数量关系以及它们的统计意义。
This paper deals with the quantitative relations between regression coefficients and partial correlation coefficients in multivariate linear regression, and their statistical meanings.
在这篇文章里，笔者主要关注当同时考察多支金融时间序列的波动时，多元GARCH模型相比于一元GARCH模型而言，对相关系数和波动性的更好的描述。
In this article, the author concerned with a better description of the volatility and correlations under multivariate GARCH model compared with univariate GARCH model.
通过多元线性回归，得出气象因子与液流速率呈极显著相关，相关系数均在0.795以上。
Though multiple regression analysis, it was showed that the correlation between SAP velocity and Meteorological Factors was highly significant and its coefficient of correlation was more than 0.795.
通过多元线性回归，得出气象因子与液流速率呈极显著相关，相关系数均在0.795以上。
Though multiple regression analysis, it was showed that the correlation between SAP velocity and Meteorological Factors was highly significant and its coefficient of correlation was more than 0.795.
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