现在如果这么命令得到
Call:
lm(formula = r ~ T * style)
Residuals:
Min 1Q Median 3Q Max
-0.138548 -0.015316 -0.002142 0.012784 0.218291
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -0.1120277 0.0122881 -9.117 < 2e-16 ***
T 0.0092829 0.0005321 17.446 < 2e-16 ***
style2 -0.0973915 0.0194299 -5.012 6.94e-07 ***
style3 -0.2196725 0.0205475 -10.691 < 2e-16 ***
style4 -0.2173575 0.0213447 -10.183 < 2e-16 ***
style5 -0.0540966 0.0217191 -2.491 0.012997 *
style6 -0.0566484 0.0221285 -2.560 0.010694 *
style7 0.0797543 0.0221285 3.604 0.000337 ***
style8 -0.0168126 0.0199744 -0.842 0.400263
T:style2 0.0064174 0.0008352 7.684 5.73e-14 ***
T:style3 0.0157410 0.0008784 17.920 < 2e-16 ***
T:style4 0.0146482 0.0009109 16.081 < 2e-16 ***
T:style5 0.0031398 0.0009255 3.393 0.000734 ***
T:style6 0.0033810 0.0009413 3.592 0.000353 ***
T:style7 -0.0068537 0.0009413 -7.281 9.65e-13 ***
T:style8 0.0014576 0.0008339 1.748 0.080956 .
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 0.03764 on 648 degrees of freedom
Multiple R-squared: 0.8991, Adjusted R-squared: 0.8968
F-statistic: 385.1 on 15 and 648 DF, p-value: < 2.2e-16
又怎么分析呢?