如题
没有attach是这样的
> model=lm(y~k+l,data=data)
> summary(model)
Call:
lm(formula = y ~ k + l, data = data)
Residuals:
Min 1Q Median 3Q Max
-1.3375 -0.1594 0.1423 0.2603 0.5335
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -1.62635 0.85695 -1.898 0.0722 .
k 1.16736 0.10888 10.722 9.68e-10 ***
l -0.07674 0.13473 -0.570 0.5753
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 0.4391 on 20 degrees of freedom
Multiple R-squared: 0.9468, Adjusted R-squared: 0.9414
F-statistic: 177.8 on 2 and 20 DF, p-value: 1.831e-13
attach出来是这样的
> model=lm(y~k+l)
> summary(model)
Call:
lm(formula = y ~ k + l)
Residuals:
Min 1Q Median 3Q Max
-0.9287 -0.3084 0.1082 0.3572 0.6941
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 0.60506 0.61594 0.982 0.334
k 0.05678 0.16406 0.346 0.732
l 0.86050 0.15906 5.410 9.05e-06 ***
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 0.4509 on 28 degrees of freedom
Multiple R-squared: 0.8458, Adjusted R-squared: 0.8348
F-statistic: 76.79 on 2 and 28 DF, p-value: 4.298e-12