cor(test2[, c("아이큐","공부시간","등급평균")])
test2 <-
test2[-1]
m2 <- lm(시험점수~.,data=test2)
m2
summary(m2)
vif(m2)
> summary(m2)
Call:
lm(formula
= 시험점수 ~ ., data = test2)
Residuals:
Min
1Q Median 3Q
Max
-6.3146 -1.2184
-0.4266 1.5516 5.6358
Coefficients:
Estimate Std. Error t value
Pr(>|t|)
(Intercept)
50.30669 35.70317 1.409
0.2085
아이큐 0.05875 0.55872
0.105 0.9197 # p-value 가 0.05 넘음
공부시간 0.48876 0.17719
2.758 0.0329 *
등급평균 7.37578 8.63161
0.855 0.4256 # p-value 가 0.05 넘음
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’
1
Residual standard
error: 3.952 on 6 degrees of freedom
Multiple
R-squared:
0.9155, Adjusted
R-squared: 0.8733
F-statistic: 21.68
on 3 and 6 DF, p-value: 0.001275
> vif(m2)
아이큐 공부시간
등급평균
22.643553 2.517786 19.658264 # 팽창계수가 10보다 크다.
# 공부시간 + 등급평균
test2 <-
read.csv("test_vif2.csv")
test2
cor(test2[,
c("아이큐","공부시간","등급평균")])
test2 <-
test2[-1]
m2
<- lm(시험점수~공부시간+등급평균,data=test2)
m2
summary(m2)
vif(m2)
> m2
Call:
lm(formula
= 시험점수 ~ 공부시간 + 등급평균, data = test2)
Coefficients:
(Intercept) 공부시간 등급평균
54.019 0.496 8.233
> summary(m2)
Call:
lm(formula
= 시험점수 ~ 공부시간 + 등급평균, data = test2)
Residuals:
Min
1Q Median 3Q
Max
-6.3179 -1.2020
-0.5051 1.3484 5.6317
Coefficients:
Estimate Std. Error t value
Pr(>|t|)
(Intercept) 54.0194
4.9092 11.004 1.14e-05 ***
공부시간 0.4960 0.1514
3.275 0.0136 *
등급평균 8.2326 2.6398
3.119 0.0169 *
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’
1
Residual standard
error: 3.662 on 7 degrees of freedom
Multiple R-squared: 0.9154, Adjusted
R-squared: 0.8912
F-statistic: 37.87
on 2 and 7 DF, p-value: 0.0001762