library(wooldridge)
## Warning: package 'wooldridge' was built under R version 4.1.3
library(rmarkdown)
## Warning: package 'rmarkdown' was built under R version 4.1.3
library(stargazer)
## 
## Please cite as:
##  Hlavac, Marek (2022). stargazer: Well-Formatted Regression and Summary Statistics Tables.
##  R package version 5.2.3. https://CRAN.R-project.org/package=stargazer
data("vote1")
paged_table(vote1)
vote<- lm(voteA~lexpendA+lexpendB+log(prtystrA),data = vote1)
summary(vote)
## 
## Call:
## lm(formula = voteA ~ lexpendA + lexpendB + log(prtystrA), data = vote1)
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
## -20.5559  -5.2695  -0.9599   4.8324  25.9264 
## 
## Coefficients:
##               Estimate Std. Error t value Pr(>|t|)    
## (Intercept)    25.6135    11.3090   2.265   0.0248 *  
## lexpendA        6.0836     0.3829  15.890   <2e-16 ***
## lexpendB       -6.6370     0.3779 -17.562   <2e-16 ***
## log(prtystrA)   6.9825     2.9010   2.407   0.0172 *  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 7.717 on 169 degrees of freedom
## Multiple R-squared:  0.7923, Adjusted R-squared:  0.7886 
## F-statistic: 214.9 on 3 and 169 DF,  p-value: < 2.2e-16

SORU1

Beta1’nin Yorumu nedir?.

cevap 1

ExpendA harcamalarındaki %1lik artış olursa %6.08 oy kazanır.

soru2

A’nin harcamalarındakı %1 lik artışın B’nin harcamalarindaki %1 lik artışla dengelendiği hipotezini parametreler cinsinden ifade ediniz ?.

cevap 2

A’nin harcamalarindaki %1lik artış olursa 6.08 oy kazaniyor ve B’deki aday 6.63 oy kaybedecek.

soru 3

Verilen modeli VOTE1.RAW’daki verileri kullanarak tahmin ediniz ve sonuçları her zamanki formda rapor ediniz.

cevap 3

paged_table(vote1)
stargazer(vote,type = "text")
## 
## ===============================================
##                         Dependent variable:    
##                     ---------------------------
##                                voteA           
## -----------------------------------------------
## lexpendA                     6.084***          
##                               (0.383)          
##                                                
## lexpendB                     -6.637***         
##                               (0.378)          
##                                                
## log(prtystrA)                 6.983**          
##                               (2.901)          
##                                                
## Constant                     25.614**          
##                              (11.309)          
##                                                
## -----------------------------------------------
## Observations                    173            
## R2                             0.792           
## Adjusted R2                    0.789           
## Residual Std. Error      7.717 (df = 169)      
## F Statistic          214.900*** (df = 3; 169)  
## ===============================================
## Note:               *p<0.1; **p<0.05; ***p<0.01

Soru 3.1

A’nin harcamalari sonucu etkiler mi ?

cevap 3.1

A’nin harcamalari sonucu etkiler çünkü aday A harcamalarının artırırsa fazla OY kazanIr.

Soru 3.2

B’nin harcamalari sonucu etkiler mi ?

cevap 3.2

B’nin harcamalari sonucu etkiler çünkü aday B harcamalarının artırırsa oy Kaybeder.

soru 3.3

Bu sonuçları(3.2)deki hipotezi test etmek için kulanabilir misiniz ?

cevap 3.3

Evet, kulanilabilir

Soru 3.4

(II)’deki hipotezi test etmek için t istatistiğini doğrudan veren bir model tahmin ediniz.Ne sonuca varırsınız?(İki taraflı alternatif kullanınız.)

CEVAP 3.4

vote<- lm(voteA~lexpendA+lexpendB+log(prtystrA),data = vote1)
summary(vote)
## 
## Call:
## lm(formula = voteA ~ lexpendA + lexpendB + log(prtystrA), data = vote1)
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
## -20.5559  -5.2695  -0.9599   4.8324  25.9264 
## 
## Coefficients:
##               Estimate Std. Error t value Pr(>|t|)    
## (Intercept)    25.6135    11.3090   2.265   0.0248 *  
## lexpendA        6.0836     0.3829  15.890   <2e-16 ***
## lexpendB       -6.6370     0.3779 -17.562   <2e-16 ***
## log(prtystrA)   6.9825     2.9010   2.407   0.0172 *  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 7.717 on 169 degrees of freedom
## Multiple R-squared:  0.7923, Adjusted R-squared:  0.7886 
## F-statistic: 214.9 on 3 and 169 DF,  p-value: < 2.2e-16
t.test(vote1$expendB, alternative = "less")
## 
##  One Sample t-test
## 
## data:  vote1$expendB
## t = 13.102, df = 172, p-value = 1
## alternative hypothesis: true mean is less than 0
## 95 percent confidence interval:
##      -Inf 343.5979
## sample estimates:
## mean of x 
##  305.0885
t.test(vote1$expendA, alternative = "less")
## 
##  One Sample t-test
## 
## data:  vote1$expendA
## t = 14.54, df = 172, p-value = 1
## alternative hypothesis: true mean is less than 0
## 95 percent confidence interval:
##      -Inf 345.9402
## sample estimates:
## mean of x 
##   310.611
library(ggplot2)
## Warning: package 'ggplot2' was built under R version 4.1.3
ggplot(vote1, aes(x=expendA, y=expendB))+geom_point()

iki taraflı alternatif

t.test(vote1$expendA, vote1$expendB, var.equal =TRUE)
## 
##  Two Sample t-test
## 
## data:  vote1$expendA and vote1$expendB
## t = 0.17476, df = 344, p-value = 0.8614
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -56.63256  67.67750
## sample estimates:
## mean of x mean of y 
##  310.6110  305.0885