Ders 1

Sıradan En Küçük Kareler Tahminlerini Elde Etme

Sıradan En Küçük Kareler, SEKK (Ordinary Least Squares, OLS), β0 ve β1’i tahmin etme.

library(wooldridge)
data("ceosal1")

library(rmarkdown)
paged_table(ceosal1)

Ortalama maaş

mean(ceosal1$salary)

## [1] 1281.12

En küçük ve en büyük maaş

min(ceosal1$salary)

## [1] 223

max(ceosal1$roe)

## [1] 56.3

Ortalama özsermaye

mean(ceosal1$roe)

## [1] 17.18421

En küçük ve en büyük özsermaye

min(ceosal1$roe)

## [1] 0.5

max(ceosal1$roe)

## [1] 56.3

lm(salary ~ roe, data = ceosal1)

## 
## Call:
## lm(formula = salary ~ roe, data = ceosal1)
## 
## Coefficients:
## (Intercept)          roe  
##       963.2         18.5

data(wage1)

mean(wage1$wage)

## [1] 5.896103

lm(wage1$wage ~ wage1$educ)

## 
## Call:
## lm(formula = wage1$wage ~ wage1$educ)
## 
## Coefficients:
## (Intercept)   wage1$educ  
##     -0.9049       0.5414

data(vote1)

lm(vote1$voteA ~ vote1$shareA)

## 
## Call:
## lm(formula = vote1$voteA ~ vote1$shareA)
## 
## Coefficients:
##  (Intercept)  vote1$shareA  
##      26.8122        0.4638