Parcial - Estadistica 2

library(rio)
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

parcial=import("dataPeru.xlsx")

str(parcial)

## '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 ...

buenEstado <- parcial$buenEstado
contribuyentesSunat <- parcial$contribuyentesSunat / parcial$pobTotal * 100
peaOcupada <- parcial$peaOcupada / parcial$pobTotal * 100

modelo <- lm(buenEstado ~ contribuyentesSunat + peaOcupada, parcial = parcial)

## Warning: In lm.fit(x, y, offset = offset, singular.ok = singular.ok, ...) :
##  extra argument 'parcial' will be disregarded

summary(modelo)

## 
## Call:
## lm(formula = buenEstado ~ contribuyentesSunat + peaOcupada, parcial = parcial)
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
## -10.0928  -4.3610   0.2575   4.4003  11.0196 
## 
## Coefficients:
##                     Estimate Std. Error t value Pr(>|t|)
## (Intercept)         -22.6095    15.9617  -1.416    0.171
## contribuyentesSunat   0.1003     0.3121   0.321    0.751
## peaOcupada            1.0218     0.6424   1.590    0.126
## 
## Residual standard error: 6.299 on 22 degrees of freedom
## Multiple R-squared:  0.4669, Adjusted R-squared:  0.4184 
## F-statistic: 9.633 on 2 and 22 DF,  p-value: 0.000989

peaOcupada <- parcial$peaOcupada
contribuyentesSunat <- parcial$contribuyentesSunat
buenEstado <- parcial$buenEstado

modelo2 <- lm(peaOcupada ~ contribuyentesSunat + buenEstado, parcial = parcial)

## Warning: In lm.fit(x, y, offset = offset, singular.ok = singular.ok, ...) :
##  extra argument 'parcial' will be disregarded

summary(modelo2)

## 
## Call:
## lm(formula = peaOcupada ~ contribuyentesSunat + buenEstado, parcial = parcial)
## 
## 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