- Al querer probar la hipotesis que el buen estado de los locales
escolares depende del porcentaje de la poblacion que contribuye a la
SUNAT; y del porcentaje de la PEA que está laborando; se llega a
comprobar que (con una significancia del 0.05):
library(rio)
data=import("dataPeru.xlsx")
str(data)
## 'data.frame': 25 obs. of 8 variables:
## $ DEPARTAMENTO : chr "AMAZONAS" "ÁNCASH" "APURÍMAC" "AREQUIPA" ...
## $ UBIGEO : chr "010000" "020000" "030000" "040000" ...
## $ buenEstado : num 18.6 13.9 8.7 27.4 17 18 33.8 11.9 10.1 15.6 ...
## $ contribuyentesSunat: num 75035 302906 103981 585628 151191 ...
## $ peaOcupada : num 130019 387976 140341 645001 235857 ...
## $ pobUrbana : num 205976 806065 243354 1383694 444473 ...
## $ PobRural : num 211389 333050 180905 76739 206467 ...
## $ pobTotal : num 417365 1139115 424259 1460433 650940 ...
modelo1=formula(buenEstado~contribuyentesSunat+peaOcupada)
reg1=lm(modelo1,data=data)
summary(reg1)
##
## Call:
## lm(formula = modelo1, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -10.589 -3.966 -1.347 1.907 21.518
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 1.865e+01 2.694e+00 6.922 5.98e-07 ***
## contribuyentesSunat 1.786e-05 2.060e-05 0.867 0.395
## peaOcupada -1.596e-05 2.241e-05 -0.712 0.484
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 7.925 on 22 degrees of freedom
## Multiple R-squared: 0.1561, Adjusted R-squared: 0.07939
## F-statistic: 2.035 on 2 and 22 DF, p-value: 0.1546
modelo1_st = formula(scale(buenEstado)~scale(contribuyentesSunat)+scale(peaOcupada))
modelo1_st = lm(modelo1_st, data = data)
summary(modelo1_st)
##
## Call:
## lm(formula = modelo1_st, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.2821 -0.4802 -0.1631 0.2309 2.6052
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 3.313e-16 1.919e-01 0.000 1.000
## scale(contribuyentesSunat) 2.034e+00 2.346e+00 0.867 0.395
## scale(peaOcupada) -1.670e+00 2.346e+00 -0.712 0.484
##
## Residual standard error: 0.9595 on 22 degrees of freedom
## Multiple R-squared: 0.1561, Adjusted R-squared: 0.07939
## F-statistic: 2.035 on 2 and 22 DF, p-value: 0.1546
- Al querer probar la hipotesis que la cantidad de PEA ocupada
dependen de la cantidad de contribuyentes a la SUNAT ; y del porcentaje
de locales escolares en buen estado; se llega a comprobar que (con una
significancia del 0.05)
modelo2=formula(peaOcupada~contribuyentesSunat+buenEstado)
reg2=lm(modelo2,data=data)
summary(reg2)
##
## Call:
## lm(formula = modelo2, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -91867 -58573 -11166 46174 155851
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 1.155e+05 3.787e+04 3.049 0.00588 **
## contribuyentesSunat 9.206e-01 1.741e-02 52.872 < 2e-16 ***
## buenEstado -1.412e+03 1.983e+03 -0.712 0.48395
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 74540 on 22 degrees of freedom
## Multiple R-squared: 0.9932, Adjusted R-squared: 0.9926
## F-statistic: 1603 on 2 and 22 DF, p-value: < 2.2e-16
library(modelsummary)
## `modelsummary` 2.0.0 now uses `tinytable` as its default table-drawing
## backend. Learn more at: https://vincentarelbundock.github.io/tinytable/
##
## Revert to `kableExtra` for one session:
##
## options(modelsummary_factory_default = 'kableExtra')
## options(modelsummary_factory_latex = 'kableExtra')
## options(modelsummary_factory_html = 'kableExtra')
##
## Silence this message forever:
##
## config_modelsummary(startup_message = FALSE)
modelo2_st = formula(scale(peaOcupada)~scale(contribuyentesSunat)+scale(buenEstado))
modelo2_st = lm(modelo2_st, data = data)
summary(modelo2_st)
##
## Call:
## lm(formula = modelo2_st, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.10626 -0.06775 -0.01292 0.05341 0.18027
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 8.043e-17 1.724e-02 0.000 1.000
## scale(contribuyentesSunat) 1.001e+00 1.894e-02 52.872 <2e-16 ***
## scale(buenEstado) -1.349e-02 1.894e-02 -0.712 0.484
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.08622 on 22 degrees of freedom
## Multiple R-squared: 0.9932, Adjusted R-squared: 0.9926
## F-statistic: 1603 on 2 and 22 DF, p-value: < 2.2e-16