library(wooldridge)

library(rmarkdown)
library(dplyr)
## 
## Attaching package: 'dplyr'
## The following objects are masked from 'package:stats':
## 
##     filter, lag
## The following objects are masked from 'package:base':
## 
##     intersect, setdiff, setequal, union

cps78_85

data("cps78_85")
head(cps78_85)
##   educ south nonwhite female married exper expersq union  lwage age year y85
## 1   12     0        0      0       0     8      64     0 1.2150  25   78   0
## 2   12     0        0      1       1    30     900     1 1.6094  47   78   0
## 3    6     0        0      0       1    38    1444     1 2.1401  49   78   0
## 4   12     0        0      0       1    19     361     1 2.0732  36   78   0
## 5   12     0        0      0       1    11     121     0 1.6490  28   78   0
## 6    8     0        0      0       1    43    1849     0 1.7148  56   78   0
##   y85fem y85educ y85union
## 1      0       0        0
## 2      0       0        0
## 3      0       0        0
## 4      0       0        0
## 5      0       0        0
## 6      0       0        0
tail(cps78_85)
##      educ south nonwhite female married exper expersq union  lwage age year y85
## 1079   17     0        1      1       1    25     625     1 3.1463  48   85   1
## 1080   12     0        1      1       1    18     324     0 2.1552  36   85   1
## 1081   14     0        0      1       0    13     169     0 2.9178  33   85   1
## 1082   18     0        0      0       1     8      64     0 3.1001  32   85   1
## 1083   12     0        1      0       0    14     196     1 2.7887  32   85   1
## 1084   12     0        0      0       0     9      81     0 2.9689  27   85   1
##      y85fem y85educ y85union
## 1079      1      17        1
## 1080      1      12        0
## 1081      1      14        0
## 1082      0      18        0
## 1083      0      12        1
## 1084      0      12        0
summary(cps78_85)
##       educ           south           nonwhite          female     
##  Min.   : 1.00   Min.   :0.0000   Min.   :0.0000   Min.   :0.000  
##  1st Qu.:12.00   1st Qu.:0.0000   1st Qu.:0.0000   1st Qu.:0.000  
##  Median :12.00   Median :0.0000   Median :0.0000   Median :0.000  
##  Mean   :12.77   Mean   :0.2943   Mean   :0.1144   Mean   :0.417  
##  3rd Qu.:14.00   3rd Qu.:1.0000   3rd Qu.:0.0000   3rd Qu.:1.000  
##  Max.   :18.00   Max.   :1.0000   Max.   :1.0000   Max.   :1.000  
##     married           exper          expersq           union       
##  Min.   :0.0000   Min.   : 0.00   Min.   :   0.0   Min.   :0.0000  
##  1st Qu.:0.0000   1st Qu.: 8.00   1st Qu.:  64.0   1st Qu.:0.0000  
##  Median :1.0000   Median :15.00   Median : 225.0   Median :0.0000  
##  Mean   :0.6541   Mean   :18.28   Mean   : 499.8   Mean   :0.2435  
##  3rd Qu.:1.0000   3rd Qu.:28.00   3rd Qu.: 784.0   3rd Qu.:0.0000  
##  Max.   :1.0000   Max.   :55.00   Max.   :3025.0   Max.   :1.0000  
##      lwage             age             year            y85        
##  Min.   :-0.470   Min.   :18.00   Min.   :78.00   Min.   :0.0000  
##  1st Qu.: 1.470   1st Qu.:27.00   1st Qu.:78.00   1st Qu.:0.0000  
##  Median : 1.833   Median :34.00   Median :78.00   Median :0.0000  
##  Mean   : 1.867   Mean   :36.54   Mean   :81.45   Mean   :0.4926  
##  3rd Qu.: 2.225   3rd Qu.:46.00   3rd Qu.:85.00   3rd Qu.:1.0000  
##  Max.   : 3.796   Max.   :64.00   Max.   :85.00   Max.   :1.0000  
##      y85fem         y85educ          y85union      
##  Min.   :0.000   Min.   : 0.000   Min.   :0.00000  
##  1st Qu.:0.000   1st Qu.: 0.000   1st Qu.:0.00000  
##  Median :0.000   Median : 0.000   Median :0.00000  
##  Mean   :0.226   Mean   : 6.413   Mean   :0.08856  
##  3rd Qu.:0.000   3rd Qu.:12.000   3rd Qu.:0.00000  
##  Max.   :1.000   Max.   :18.000   Max.   :1.00000

paket yükleme

paged_table(cps78_85)
cps78_85 %>% 
  group_by(year) %>% 
  summarise(sayı = n())
## # A tibble: 2 × 2
##    year  sayı
##   <int> <int>
## 1    78   550
## 2    85   534
summary(lm(lwage ~ y85+(educ + female) + exper + I(exper^2) + union, data = cps78_85))
## 
## Call:
## lm(formula = lwage ~ y85 + (educ + female) + exper + I(exper^2) + 
##     union, data = cps78_85)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -2.5438 -0.2606  0.0085  0.2693  2.1522 
## 
## Coefficients:
##               Estimate Std. Error t value Pr(>|t|)    
## (Intercept)  3.322e-01  7.549e-02   4.400 1.19e-05 ***
## y85          3.900e-01  2.556e-02  15.260  < 2e-16 ***
## educ         8.333e-02  5.069e-03  16.438  < 2e-16 ***
## female      -2.747e-01  2.583e-02 -10.638  < 2e-16 ***
## exper        2.968e-02  3.573e-03   8.306 2.94e-16 ***
## I(exper^2)  -3.982e-04  7.771e-05  -5.124 3.54e-07 ***
## union        2.043e-01  3.032e-02   6.739 2.59e-11 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 0.4136 on 1077 degrees of freedom
## Multiple R-squared:  0.4225, Adjusted R-squared:  0.4193 
## F-statistic: 131.3 on 6 and 1077 DF,  p-value: < 2.2e-16
summary(lm(lwage ~ y85 + y85fem +(educ + female) + exper + I(exper^2) + union - 1, data = cps78_85))
## 
## Call:
## lm(formula = lwage ~ y85 + y85fem + (educ + female) + exper + 
##     I(exper^2) + union - 1, data = cps78_85)
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
## -2.56491 -0.24219  0.02137  0.27814  2.16737 
## 
## Coefficients:
##              Estimate Std. Error t value Pr(>|t|)    
## y85         3.793e-01  3.315e-02  11.443  < 2e-16 ***
## y85fem      5.230e-02  5.123e-02   1.021    0.308    
## educ        1.035e-01  2.566e-03  40.342  < 2e-16 ***
## female     -2.868e-01  3.629e-02  -7.904 6.66e-15 ***
## exper       3.423e-02  3.452e-03   9.915  < 2e-16 ***
## I(exper^2) -4.465e-04  7.763e-05  -5.753 1.14e-08 ***
## union       2.205e-01  3.039e-02   7.256 7.63e-13 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 0.4171 on 1077 degrees of freedom
## Multiple R-squared:  0.9543, Adjusted R-squared:  0.954 
## F-statistic:  3211 on 7 and 1077 DF,  p-value: < 2.2e-16
benimdata <- cps78_85 %>% 
   mutate(sabitim = ifelse(married == 1 ,0 ,1))
summary(lm(benimdata))
## 
## Call:
## lm(formula = benimdata)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -0.0778 -0.0143 -0.0033  0.0077  3.9201 
## 
## Coefficients: (2 not defined because of singularities)
##               Estimate Std. Error  t value Pr(>|t|)    
## (Intercept)  7.178e+00  4.216e-01   17.026   <2e-16 ***
## south       -4.977e-03  8.312e-03   -0.599   0.5495    
## nonwhite    -6.889e-04  1.187e-02   -0.058   0.9537    
## female       3.980e-03  1.126e-02    0.353   0.7239    
## married     -6.250e-03  8.408e-03   -0.743   0.4574    
## exper       -9.972e-01  2.353e-03 -423.803   <2e-16 ***
## expersq      4.442e-05  2.360e-05    1.882   0.0601 .  
## union       -3.296e-03  1.173e-02   -0.281   0.7787    
## lwage        1.636e-02  9.002e-03    1.817   0.0695 .  
## age          9.946e-01  2.071e-03  480.192   <2e-16 ***
## year        -1.549e-01  5.115e-03  -30.281   <2e-16 ***
## y85                 NA         NA       NA       NA    
## y85fem       1.663e-02  1.532e-02    1.086   0.2778    
## y85educ      6.584e-03  2.751e-03    2.394   0.0169 *  
## y85union    -2.665e-03  1.791e-02   -0.149   0.8818    
## sabitim             NA         NA       NA       NA    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 0.1211 on 1070 degrees of freedom
## Multiple R-squared:  0.998,  Adjusted R-squared:  0.998 
## F-statistic: 4.153e+04 on 13 and 1070 DF,  p-value: < 2.2e-16
summary(benimdata)
##       educ           south           nonwhite          female     
##  Min.   : 1.00   Min.   :0.0000   Min.   :0.0000   Min.   :0.000  
##  1st Qu.:12.00   1st Qu.:0.0000   1st Qu.:0.0000   1st Qu.:0.000  
##  Median :12.00   Median :0.0000   Median :0.0000   Median :0.000  
##  Mean   :12.77   Mean   :0.2943   Mean   :0.1144   Mean   :0.417  
##  3rd Qu.:14.00   3rd Qu.:1.0000   3rd Qu.:0.0000   3rd Qu.:1.000  
##  Max.   :18.00   Max.   :1.0000   Max.   :1.0000   Max.   :1.000  
##     married           exper          expersq           union       
##  Min.   :0.0000   Min.   : 0.00   Min.   :   0.0   Min.   :0.0000  
##  1st Qu.:0.0000   1st Qu.: 8.00   1st Qu.:  64.0   1st Qu.:0.0000  
##  Median :1.0000   Median :15.00   Median : 225.0   Median :0.0000  
##  Mean   :0.6541   Mean   :18.28   Mean   : 499.8   Mean   :0.2435  
##  3rd Qu.:1.0000   3rd Qu.:28.00   3rd Qu.: 784.0   3rd Qu.:0.0000  
##  Max.   :1.0000   Max.   :55.00   Max.   :3025.0   Max.   :1.0000  
##      lwage             age             year            y85        
##  Min.   :-0.470   Min.   :18.00   Min.   :78.00   Min.   :0.0000  
##  1st Qu.: 1.470   1st Qu.:27.00   1st Qu.:78.00   1st Qu.:0.0000  
##  Median : 1.833   Median :34.00   Median :78.00   Median :0.0000  
##  Mean   : 1.867   Mean   :36.54   Mean   :81.45   Mean   :0.4926  
##  3rd Qu.: 2.225   3rd Qu.:46.00   3rd Qu.:85.00   3rd Qu.:1.0000  
##  Max.   : 3.796   Max.   :64.00   Max.   :85.00   Max.   :1.0000  
##      y85fem         y85educ          y85union          sabitim      
##  Min.   :0.000   Min.   : 0.000   Min.   :0.00000   Min.   :0.0000  
##  1st Qu.:0.000   1st Qu.: 0.000   1st Qu.:0.00000   1st Qu.:0.0000  
##  Median :0.000   Median : 0.000   Median :0.00000   Median :0.0000  
##  Mean   :0.226   Mean   : 6.413   Mean   :0.08856   Mean   :0.3459  
##  3rd Qu.:0.000   3rd Qu.:12.000   3rd Qu.:0.00000   3rd Qu.:1.0000  
##  Max.   :1.000   Max.   :18.000   Max.   :1.00000   Max.   :1.0000