CPS96_15
enara
2025-05-22
## Warning: package 'Rcmdr' was built under R version 4.4.3
## Cargando paquete requerido: splines
## Cargando paquete requerido: RcmdrMisc
## Cargando paquete requerido: car
## Cargando paquete requerido: carData
## Cargando paquete requerido: sandwich
## Cargando paquete requerido: effects
## lattice theme set by effectsTheme()
## See ?effectsTheme for details.
## La interfaz R-Commander sólo funciona en sesiones interactivas
##
## Adjuntando el paquete: 'Rcmdr'
## The following object is masked from 'package:base':
##
## errorCondition
> CPS96_15. <-
+ readXL("C:/Users/enara/Documents/ADE (USAL)/ECONOMETRÍA/CPS96_15 TRABAJAR BASE DE DATOS BRECHA DE GÉNERO EN INGRESOS SALARIALES.xlsx",
+ rownames=FALSE, header=TRUE, na="", sheet="Sheet1", stringsAsFactors=TRUE)
Resumir el conjunto de datos: CPS96_15.
> summary(CPS96_15.)
year ahe bachelor female
Min. :1996 Min. : 1.36 Min. :0.0000 Min. :0.0000
1st Qu.:1996 1st Qu.: 10.10 1st Qu.:0.0000 1st Qu.:0.0000
Median :2015 Median : 14.42 Median :0.0000 Median :0.0000
Mean :2006 Mean : 17.29 Mean :0.4812 Mean :0.4172
3rd Qu.:2015 3rd Qu.: 21.15 3rd Qu.:1.0000 3rd Qu.:1.0000
Max. :2015 Max. :105.77 Max. :1.0000 Max. :1.0000
age
Min. :25.00
1st Qu.:27.00
Median :30.00
Mean :29.62
3rd Qu.:32.00
Max. :34.00
> library(abind, pos=16)
> library(e1071, pos=17)
Resúmenes numéricos: CPS96_15.
> numSummary(CPS96_15.[,"bachelor", drop=FALSE], statistics=c("mean", "sd", "IQR", "quantiles"), quantiles=c(0,.25,
+ .5,.75,1))
mean sd IQR 0% 25% 50% 75% 100% n
0.4811757 0.4996644 1 0 0 0 1 1 13201
Histograma: bachelor
> with(CPS96_15., Hist(bachelor, scale="frequency", breaks="Sturges", col="darkgray"))
Histograma: ahe
> with(CPS96_15., Hist(ahe, scale="frequency", breaks="Sturges", col="darkgray"))
> data(Prestige, package="carData")
Modelo lineal: LinearModel.1: prestige ~ (education
+log(income))*type
> LinearModel.1 <- lm(prestige ~ (education +log(income))*type, data=Prestige)
> summary(LinearModel.1)
Call:
lm(formula = prestige ~ (education + log(income)) * type, data = Prestige)
Residuals:
Min 1Q Median 3Q Max
-13.970 -4.124 1.206 3.829 18.059
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -120.0459 20.1576 -5.955 5.07e-08 ***
education 2.3357 0.9277 2.518 0.01360 *
log(income) 15.9825 2.6059 6.133 2.32e-08 ***
typeprof 85.1601 31.1810 2.731 0.00761 **
typewc 30.2412 37.9788 0.796 0.42800
education:typeprof 0.6974 1.2895 0.541 0.58998
education:typewc 3.6400 1.7589 2.069 0.04140 *
log(income):typeprof -9.4288 3.7751 -2.498 0.01434 *
log(income):typewc -8.1556 4.4029 -1.852 0.06730 .
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 6.409 on 89 degrees of freedom
(4 observations deleted due to missingness)
Multiple R-squared: 0.871, Adjusted R-squared: 0.8595
F-statistic: 75.15 on 8 and 89 DF, p-value: < 2.2e-16
Modelo lineal: LinearModel.2: prestige ~ (education + log(income)) *
type
> LinearModel.2 <- lm(prestige ~ (education + log(income)) * type, data=Prestige)
> summary(LinearModel.2)
Call:
lm(formula = prestige ~ (education + log(income)) * type, data = Prestige)
Residuals:
Min 1Q Median 3Q Max
-13.970 -4.124 1.206 3.829 18.059
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -120.0459 20.1576 -5.955 5.07e-08 ***
education 2.3357 0.9277 2.518 0.01360 *
log(income) 15.9825 2.6059 6.133 2.32e-08 ***
typeprof 85.1601 31.1810 2.731 0.00761 **
typewc 30.2412 37.9788 0.796 0.42800
education:typeprof 0.6974 1.2895 0.541 0.58998
education:typewc 3.6400 1.7589 2.069 0.04140 *
log(income):typeprof -9.4288 3.7751 -2.498 0.01434 *
log(income):typewc -8.1556 4.4029 -1.852 0.06730 .
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 6.409 on 89 degrees of freedom
(4 observations deleted due to missingness)
Multiple R-squared: 0.871, Adjusted R-squared: 0.8595
F-statistic: 75.15 on 8 and 89 DF, p-value: < 2.2e-16
Análisis de varianza: LinearModel.2
> Anova(LinearModel.2, type="II")
Anova Table (Type II tests)
Response: prestige
Sum Sq Df F value Pr(>F)
education 1209.3 1 29.4446 4.912e-07 ***
log(income) 1690.8 1 41.1670 6.589e-09 ***
type 469.1 2 5.7103 0.004642 **
education:type 178.8 2 2.1762 0.119474
log(income):type 290.3 2 3.5344 0.033338 *
Residuals 3655.4 89
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1