ödev 2

library(wooldridge)
mean(wage1$wage)

## [1] 5.896103

library(wooldridge)
lm(wage1$wage ~ wage1$educ)

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

library(wooldridge)
roe_15 <- ceosal1$roe[1:15]
roe_15

##  [1] 14.1 10.9 23.5  5.9 13.8 20.0 16.4 16.3 10.5 26.3 25.9 26.8 14.8 22.3 56.3

library(wooldridge)
salary_15 <- ceosal1$salary[1:15]
salary_15

##  [1] 1095 1001 1122  578 1368 1145 1078 1094 1237  833  567  933 1339  937 2011

library(wooldridge)
Tablo2_2 <- cbind(roe_15, salary_15)
Tablo2_2

##       roe_15 salary_15
##  [1,]   14.1      1095
##  [2,]   10.9      1001
##  [3,]   23.5      1122
##  [4,]    5.9       578
##  [5,]   13.8      1368
##  [6,]   20.0      1145
##  [7,]   16.4      1078
##  [8,]   16.3      1094
##  [9,]   10.5      1237
## [10,]   26.3       833
## [11,]   25.9       567
## [12,]   26.8       933
## [13,]   14.8      1339
## [14,]   22.3       937
## [15,]   56.3      2011

summary(cars)

##      speed           dist       
##  Min.   : 4.0   Min.   :  2.00  
##  1st Qu.:12.0   1st Qu.: 26.00  
##  Median :15.0   Median : 36.00  
##  Mean   :15.4   Mean   : 42.98  
##  3rd Qu.:19.0   3rd Qu.: 56.00  
##  Max.   :25.0   Max.   :120.00

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