homework

Örnek3.1 Kolej Gpa’sının Belirleyicileri

library(wooldridge)
data(gpa1)
library(rmarkdown)
paged_table(gpa1)

coklureg <- lm(colGPA~ hsGPA+ACT,data = gpa1)
summary(coklureg)

## 
## Call:
## lm(formula = colGPA ~ hsGPA + ACT, data = gpa1)
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
## -0.85442 -0.24666 -0.02614  0.28127  0.85357 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept) 1.286328   0.340822   3.774 0.000238 ***
## hsGPA       0.453456   0.095813   4.733 5.42e-06 ***
## ACT         0.009426   0.010777   0.875 0.383297    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 0.3403 on 138 degrees of freedom
## Multiple R-squared:  0.1764, Adjusted R-squared:  0.1645 
## F-statistic: 14.78 on 2 and 138 DF,  p-value: 1.526e-06

Basit regresyon örneğimizi hatırlarsak

basitreg <- lm(colGPA~ACT,data = gpa1)
summary(basitreg)

## 
## Call:
## lm(formula = colGPA ~ ACT, data = gpa1)
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
## -0.85251 -0.25251 -0.04426  0.26400  0.89336 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)  2.40298    0.26420   9.095  8.8e-16 ***
## ACT          0.02706    0.01086   2.491   0.0139 *  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 0.3656 on 139 degrees of freedom
## Multiple R-squared:  0.04275,    Adjusted R-squared:  0.03586 
## F-statistic: 6.207 on 1 and 139 DF,  p-value: 0.0139