为啥哪都有你

看完觉得自己计量白学了……

一点想法：回归得到的是系数的【估计值】，也就是系数作为一个【本来应该是数值】的量，在当前置信水平下的估计值而已

个人理解，系数存在一个“真实值”， 但我们做估计时并不能确认模型得到的一定就是真实值，而是估计值，系数检验只是在给定的数据模型结果下做出一个大致概率判断。基本同楼上观点。

Classical inference emphasizes the existence of "constant" parameters to drive the model. However, since the estimate of Beta is dependent on the sample, so it's a random variable; the concept of sampling distribution. Depends on the assumption used in the error term, e.g., iid normal, or using the Central limit Theorem, the estimate of beta has a nice distribution (normal), so we can easily derive a t-test. The expected Y, not Y, is also a random variable because it's a product of estimated beta and given X (assumed it's fixed in a controlled experiment, which is not usually).