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> body.fit3<-lm(height~chest+waist+thigh+calf+bicep+ wrist+weight+gender)
> summary(body.fit3)
Call:
lm(formula = height ~ chest + waist + thigh + calf + bicep +
wrist + weight + gender)
Residuals:
Min 1Q Median 3Q Max
-14.1845 -2.6721 0.2656 2.6787 14.2525
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 213.32496 6.45815 33.032 < 2e-16 ***
chest -0.15178 0.06884 -2.205 0.0280 *
waist -0.66706 0.05725 -11.652 < 2e-16 ***
thigh -0.58953 0.09730 -6.059 3.07e-09 ***
calf -0.62432 0.13233 -4.718 3.26e-06 ***
bicep -1.02794 0.14782 -6.954 1.39e-11 ***
wrist 0.63009 0.36441 1.729 0.0845 .
weight 1.42233 0.06371 22.324 < 2e-16 ***
gender 6.22182 0.95690 6.502 2.28e-10 ***
---
Signif. codes: 0 ¡®***¡¯ 0.001 ¡®**¡¯ 0.01 ¡®*¡¯ 0.05 ¡®.¡¯ 0.1 ¡® ¡¯ 1
Residual standard error: 4.238 on 415 degrees of freedom
Multiple R-Squared: 0.8004, Adjusted R-squared: 0.7966
F-statistic: 208.1 on 8 and 415 DF, p-value: < 2.2e-16
> body.fit4<-lm(height~chest+waist+thigh+calf+bicep+weight+gender)
> summary(body.fit4)
Call:
lm(formula = height ~ chest + waist + thigh + calf + bicep +
weight + gender)
Residuals:
Min 1Q Median 3Q Max
-14.0463 -2.5778 0.2107 2.6500 14.5224
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 219.84440 5.25569 41.830 < 2e-16 ***
chest -0.14062 0.06870 -2.047 0.0413 *
waist -0.69218 0.05551 -12.470 < 2e-16 ***
thigh -0.63483 0.09393 -6.759 4.72e-11 ***
calf -0.56458 0.12804 -4.409 1.32e-05 ***
bicep -0.94860 0.14086 -6.735 5.48e-11 ***
weight 1.45568 0.06087 23.915 < 2e-16 ***
gender 6.49949 0.94558 6.874 2.30e-11 ***
---
Signif. codes: 0 ¡®***¡¯ 0.001 ¡®**¡¯ 0.01 ¡®*¡¯ 0.05 ¡®.¡¯ 0.1 ¡® ¡¯ 1
Residual standard error: 4.248 on 416 degrees of freedom
Multiple R-Squared: 0.799, Adjusted R-squared: 0.7956
F-statistic: 236.2 on 7 and 416 DF, p-value: < 2.2e-16
DROP wrist之后。。。Multiple R-Squared 和Adjusted R-squared都变小了~- -!
而且。。> resid.plot(body.fit3) P-VALUE=0。0572(BEFORE DROP WRIST)
> resid.plot(body.fit4)=0。0357 (AFTER DROP WRIST)
那是不是代表不需要DROP WRIST? |
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