可能重复：
如何引用回归模型的系数标准误差？

如果我有一个数据集：

data = data.frame(xdata = 1:10,ydata = 6:15)

我运行线性回归：

fit = lm(ydata~.,data = data)
out = summary(fit)

Call:
lm(formula = ydata ~ ., data = data)

Residuals:
       Min         1Q     Median         3Q        Max 
-5.661e-16 -1.157e-16  4.273e-17  2.153e-16  4.167e-16 

Coefficients:
             Estimate Std. Error   t value Pr(>|t|)    
(Intercept) 5.000e+00  2.458e-16 2.035e+16   <2e-16 ***
xdata       1.000e+00  3.961e-17 2.525e+16   <2e-16 ***
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 

Residual standard error: 3.598e-16 on 8 degrees of freedom
Multiple R-squared:     1,  Adjusted R-squared:     1 
F-statistic: 6.374e+32 on 1 and 8 DF,  p-value: < 2.2e-16 

如何从拟合或拟合中提取回归系数的标准误差？我似乎无法弄清楚。谢谢！