应用回归分析，第4章，思考与练习，答案，r语音代码

4.8

library(readr)
data4_3 <- read_csv("data4.3.csv")
View(data4_3)
lm4.3<-lm(y~x,data = data4_3)
summary(lm4.3)

Call:
lm(formula = y ~ x, data = data4_3)

Residuals:
   Min     1Q Median     3Q    Max 
-499.8 -152.5  -25.1  174.7  452.1 

Coefficients:
              Estimate Std. Error t value Pr(>|t|)    
(Intercept) -6.481e+02  1.182e+02  -5.485  6.6e-06 ***
x            8.467e-02  4.882e-03  17.342  < 2e-16 ***
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 247.6 on 29 degrees of freedom
Multiple R-squared:  0.912,	Adjusted R-squared:  0.909 
F-statistic: 300.7 on 1 and 29 DF,  p-value: < 2.2e-16

e<-resid(lm4.3)
attach(data4_3)
plot(x,e,ylim =