生产实践和科学研究中,遇到的变量之间的关系,常可分为两大类。一类为确定性的关系,即对变量 x(称为自变量)的每一数值,变量 y(称为因变量)有一完全确定的数值与之对应,这种关系称函数关系。另一类为非确定性的关系,即变量 y 和 x 之间的取值有关系,但这种关系由于种种原因并没有密切到可以唯一确定的程度,这种关系称相关关系。变量间的相关关系,常采用相关分析和回归分析的方法进行研究。而回归分析是更为重要的方法,它已形成为统计学中重要的分支学科之一。回归分析中因变量 y是随机变量,而自变量 x 可以是随机的,也可以是非随机的变量。研究中经常将 x 视之 Production practice and scientific research, the relationship between the variables encountered can often be divided into two broad categories. One for the deterministic relationship, that is, for each value of the variable x (called the independent variable), the variable y (called the dependent variable) has a fully determined value corresponding to this relationship is called the relationship. The other is nondeterministic, that is, the relationship between the values ​​of variables y and x has a relationship that is not closely related to one another for a variety of reasons. The correlation between variables, often using correlation analysis and regression analysis methods to study. Regression analysis is a more important method, which has become one of the important branch disciplines in statistics. In the regression analysis, the dependent variable y is a random variable, and the independent variable x can be a random variable or a non-random variable. X in the study often see it