问题的建模可以简单如下图所示： 线性回归可以分为单变量线性回归(Linear Regression with One Variable)以及多变量线性回归(Linear Regression with Mul 线性回归 线性回归（Linear Regression)作为Machine Learning 整个课程的切入例...
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此外，本文提出的LQ定理使我们能用相关分析法，通过变量变换，把单因素非线性回归问题，化成线性形成来处理。
Besides, the LQ theorem presented in this paper can be used to change a nonlinear single regression problem to a linear one by means of transformation of variables.
实证部分主要包括多变量检验、单变量t检验、趋势图分析以及多元线性回归分析等。
Evidences include some of the major multi-variable tests, a single variable t tests, trend analysis and multiple linear regression analysis.
数据处理方法包括单因素多变量方差分析、多因素线性回归分析和t检验。
The data were treated with univariate and multivariate analysis of variance, multiple linear regression analysis and t test.
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