在建立回归模型或相关模型时,必须意识到,这两种模型都属于正态总体模型。区别在于:回归模型中,x是可以人为设计确定的变量,能被控制到误差很小乃至可以忽略;而y是不能人为精确控制的随机变量,有其概率分布和随机误差。回归方程就是以x为输入,y为输出的予测模型。在相关模型中x和y都是不能人为地精确控制的随 When building a regression model or related model, you must be aware that both models belong to the normal population model. The difference is that in the regression model, x is a variable that can be determined by human design and can be controlled until the error is small or even negligible; and y is a random variable that can not be artificially controlled with its probability distribution and random error. Regression equation is to x as input, y is the output of the predictive model. In the correlation model, both x and y are inaccurately controlled