Expansión de la CASEN sobre el CENSO (Región 04)

De ingresos sobre una categoría de respuesta

DataIntelligence

Abstract

Expandiremos los ingresos promedios comunales obtenidos de la CASEN sobre la categoría de respuesta: “tejas o tejuelas de arcilla, metálicas, de cemento, de madera, asfálticas o plásticas” del campo P03B del CENSO de viviendas, que fue la categoría de respuesta que más alto correlaciona con los ingresos expandidos (obtenidos de la multiplicación del ingreso promedio y los habitantes), ambos a nivel comunal.

Haremos el análisis sobre la región 01.

Ensayaremos diferentes modelos dentro del análisis de regresión cuya variable independiente será: “frecuencia de población que posee la variable Censal respecto a la zona” y la dependiente: “ingreso expandido por zona”

Lo anterior para elegir el que posea el mayor coeficiente de determinación y así contruir una tabla de valores predichos.

1 Variable CENSO

Necesitamos calcular las frecuencias a nivel censal de las respuestas correspondientes a la categoría: “tejas o tejuelas de arcilla, metálicas, de cemento, de madera, asfálticas o plásticas” del campo P03B del Censo de viviendas. Recordemos que ésta fué la más alta correlación en relación a los ingresos expandidos (ver punto 1.2 aquí).

1.1 Lectura y filtrado de la tabla censal de viviendas

Leemos la tabla Casen 2017 de viviendas que ya tiene integrada la clave zonal:

tabla_con_clave <- readRDS("censo_viviendas_con_clave_17.rds")
r3_100 <- tabla_con_clave[c(1:100),]
kbl(r3_100) %>%
  kable_styling(bootstrap_options = c("striped", "hover")) %>%
  kable_paper() %>%
  scroll_box(width = "100%", height = "300px")

REGION	PROVINCIA	COMUNA	DC	AREA	ZC_LOC	ID_ZONA_LOC	NVIV	P01	P02	P03A	P03B	P03C	P04	P05	CANT_HOG	CANT_PER	REGION_15R	PROVINCIA_15R	COMUNA_15R	clave
15	152	15202	1	2	6	13225	1	3	1	5	3	5	1	4	1	1	15	152	15202	15202012006
15	152	15202	1	2	6	13225	2	1	3	98	98	98	98	98	0	0	15	152	15202	15202012006
15	152	15202	1	2	6	13225	3	1	1	5	3	5	2	3	1	4	15	152	15202	15202012006
15	152	15202	1	2	6	13225	4	1	4	98	98	98	98	98	0	0	15	152	15202	15202012006
15	152	15202	1	2	6	13225	5	3	4	98	98	98	98	98	0	0	15	152	15202	15202012006
15	152	15202	1	2	6	13225	6	3	4	98	98	98	98	98	0	0	15	152	15202	15202012006
15	152	15202	1	2	6	13225	7	3	4	98	98	98	98	98	0	0	15	152	15202	15202012006
15	152	15202	1	2	6	13225	8	3	3	98	98	98	98	98	0	0	15	152	15202	15202012006
15	152	15202	1	2	6	13225	9	3	1	5	3	5	1	4	1	4	15	152	15202	15202012006
15	152	15202	1	2	6	13225	10	1	1	5	3	4	1	4	1	1	15	152	15202	15202012006
15	152	15202	1	2	6	13225	11	1	2	98	98	98	98	98	0	0	15	152	15202	15202012006
15	152	15202	1	2	6	13225	12	1	4	98	98	98	98	98	0	0	15	152	15202	15202012006
15	152	15202	1	2	6	13225	13	1	1	5	3	4	1	4	1	3	15	152	15202	15202012006
15	152	15202	1	2	6	13225	14	1	3	98	98	98	98	98	0	0	15	152	15202	15202012006
15	152	15202	1	2	6	13225	15	1	4	98	98	98	98	98	0	0	15	152	15202	15202012006
15	152	15202	1	2	6	13225	16	1	1	5	3	5	1	3	1	3	15	152	15202	15202012006
15	152	15202	1	2	6	13225	17	1	1	5	3	5	2	4	1	8	15	152	15202	15202012006
15	152	15202	1	2	6	13225	18	3	1	5	3	5	1	1	1	1	15	152	15202	15202012006
15	152	15202	1	2	6	13225	19	3	1	5	3	5	1	3	1	1	15	152	15202	15202012006
15	152	15202	1	2	6	13225	20	1	1	5	3	5	2	1	1	2	15	152	15202	15202012006
15	152	15202	1	2	6	13225	21	1	4	98	98	98	98	98	0	0	15	152	15202	15202012006
15	152	15202	1	2	6	13225	22	1	4	98	98	98	98	98	0	0	15	152	15202	15202012006
15	152	15202	1	2	6	13225	23	3	4	98	98	98	98	98	0	0	15	152	15202	15202012006
15	152	15202	1	2	6	13225	24	1	3	98	98	98	98	98	0	0	15	152	15202	15202012006
15	152	15202	1	2	6	13225	25	1	1	5	3	5	1	4	1	2	15	152	15202	15202012006
15	152	15202	1	2	6	13225	26	1	4	98	98	98	98	98	0	0	15	152	15202	15202012006
15	152	15202	1	2	6	13225	27	3	4	98	98	98	98	98	0	0	15	152	15202	15202012006
15	152	15202	1	2	6	13225	28	3	1	5	3	5	1	4	1	5	15	152	15202	15202012006
15	152	15202	1	2	6	13225	29	1	4	98	98	98	98	98	0	0	15	152	15202	15202012006
15	152	15202	1	2	6	13225	30	3	4	98	98	98	98	98	0	0	15	152	15202	15202012006
15	152	15202	1	2	6	13225	31	1	3	98	98	98	98	98	0	0	15	152	15202	15202012006
15	152	15202	1	2	6	13225	32	3	4	98	98	98	98	98	0	0	15	152	15202	15202012006
15	152	15202	1	2	6	13225	33	1	1	5	3	5	3	4	1	4	15	152	15202	15202012006
15	152	15202	1	2	6	13225	34	1	4	98	98	98	98	98	0	0	15	152	15202	15202012006
15	152	15202	1	2	6	13225	35	3	4	98	98	98	98	98	0	0	15	152	15202	15202012006
15	152	15202	1	2	6	13225	36	1	1	5	3	5	3	2	1	9	15	152	15202	15202012006
15	152	15202	1	2	6	13225	37	3	3	98	98	98	98	98	0	0	15	152	15202	15202012006
15	152	15202	1	2	6	13225	38	1	1	5	3	5	99	4	1	1	15	152	15202	15202012006
15	152	15202	1	2	6	13225	39	1	1	5	3	5	1	4	1	2	15	152	15202	15202012006
15	152	15202	1	2	6	13225	40	1	3	98	98	98	98	98	0	0	15	152	15202	15202012006
15	152	15202	1	2	6	13225	41	1	3	98	98	98	98	98	0	0	15	152	15202	15202012006
15	152	15202	1	2	6	13225	42	3	3	98	98	98	98	98	0	0	15	152	15202	15202012006
15	152	15202	1	2	6	13225	43	3	1	5	3	5	2	1	1	5	15	152	15202	15202012006
15	152	15202	1	2	6	13225	44	1	4	98	98	98	98	98	0	0	15	152	15202	15202012006
15	152	15202	1	2	6	13225	45	1	4	98	98	98	98	98	0	0	15	152	15202	15202012006
15	152	15202	1	2	8	13910	1	1	2	98	98	98	98	98	0	0	15	152	15202	15202012008
15	152	15202	1	2	8	13910	2	1	3	98	98	98	98	98	0	0	15	152	15202	15202012008
15	152	15202	1	2	8	13910	3	1	3	98	98	98	98	98	0	0	15	152	15202	15202012008
15	152	15202	1	2	8	13910	4	3	3	98	98	98	98	98	0	0	15	152	15202	15202012008
15	152	15202	1	2	8	13910	5	3	1	5	3	5	2	3	1	3	15	152	15202	15202012008
15	152	15202	1	2	8	13910	6	1	2	98	98	98	98	98	0	0	15	152	15202	15202012008
15	152	15202	1	2	8	13910	7	1	1	5	99	5	2	4	1	2	15	152	15202	15202012008
15	152	15202	1	2	8	13910	8	3	1	5	3	5	3	3	1	2	15	152	15202	15202012008
15	152	15202	1	2	8	13910	9	3	3	98	98	98	98	98	0	0	15	152	15202	15202012008
15	152	15202	1	2	8	13910	10	3	3	98	98	98	98	98	0	0	15	152	15202	15202012008
15	152	15202	1	2	8	13910	11	1	4	98	98	98	98	98	0	0	15	152	15202	15202012008
15	152	15202	1	2	8	13910	12	1	2	98	98	98	98	98	0	0	15	152	15202	15202012008
15	152	15202	1	2	8	13910	13	1	4	98	98	98	98	98	0	0	15	152	15202	15202012008
15	152	15202	1	2	8	13910	14	3	3	98	98	98	98	98	0	0	15	152	15202	15202012008
15	152	15202	1	2	8	13910	15	1	4	98	98	98	98	98	0	0	15	152	15202	15202012008
15	152	15202	1	2	8	13910	16	1	4	98	98	98	98	98	0	0	15	152	15202	15202012008
15	152	15202	1	2	8	13910	17	3	2	98	98	98	98	98	0	0	15	152	15202	15202012008
15	152	15202	1	2	8	13910	18	1	2	98	98	98	98	98	0	0	15	152	15202	15202012008
15	152	15202	1	2	8	13910	19	3	1	99	99	99	99	99	1	1	15	152	15202	15202012008
15	152	15202	1	2	8	13910	20	1	2	98	98	98	98	98	0	0	15	152	15202	15202012008
15	152	15202	1	2	8	13910	21	1	1	5	3	5	1	4	1	2	15	152	15202	15202012008
15	152	15202	1	2	8	13910	22	3	1	5	3	5	2	4	1	1	15	152	15202	15202012008
15	152	15202	1	2	8	13910	23	1	4	98	98	98	98	98	0	0	15	152	15202	15202012008
15	152	15202	1	2	8	13910	24	3	4	98	98	98	98	98	0	0	15	152	15202	15202012008
15	152	15202	1	2	8	13910	25	3	3	98	98	98	98	98	0	0	15	152	15202	15202012008
15	152	15202	1	2	8	13910	26	1	2	98	98	98	98	98	0	0	15	152	15202	15202012008
15	152	15202	1	2	8	13910	27	1	4	98	98	98	98	98	0	0	15	152	15202	15202012008
15	152	15202	1	2	8	13910	28	3	2	98	98	98	98	98	0	0	15	152	15202	15202012008
15	152	15202	1	2	8	13910	29	1	3	98	98	98	98	98	0	0	15	152	15202	15202012008
15	152	15202	1	2	8	13910	30	1	1	5	1	4	2	4	1	1	15	152	15202	15202012008
15	152	15202	1	2	12	8394	1	3	4	98	98	98	98	98	0	0	15	152	15202	15202012012
15	152	15202	1	2	12	8394	2	3	4	98	98	98	98	98	0	0	15	152	15202	15202012012
15	152	15202	1	2	12	8394	3	3	1	5	3	5	2	3	1	4	15	152	15202	15202012012
15	152	15202	1	2	12	8394	4	3	2	98	98	98	98	98	0	0	15	152	15202	15202012012
15	152	15202	1	2	12	8394	5	3	3	98	98	98	98	98	0	0	15	152	15202	15202012012
15	152	15202	1	2	12	8394	6	3	3	98	98	98	98	98	0	0	15	152	15202	15202012012
15	152	15202	1	2	12	8394	7	3	4	98	98	98	98	98	0	0	15	152	15202	15202012012
15	152	15202	1	2	12	8394	8	3	2	98	98	98	98	98	0	0	15	152	15202	15202012012
15	152	15202	1	2	12	8394	9	3	1	5	3	5	1	4	1	1	15	152	15202	15202012012
15	152	15202	1	2	12	8394	10	3	4	98	98	98	98	98	0	0	15	152	15202	15202012012
15	152	15202	1	2	12	8394	11	3	2	98	98	98	98	98	0	0	15	152	15202	15202012012
15	152	15202	1	2	12	8394	12	3	4	98	98	98	98	98	0	0	15	152	15202	15202012012
15	152	15202	1	2	12	8394	13	3	4	98	98	98	98	98	0	0	15	152	15202	15202012012
15	152	15202	1	2	12	8394	14	3	2	98	98	98	98	98	0	0	15	152	15202	15202012012
15	152	15202	1	2	12	8394	15	3	2	98	98	98	98	98	0	0	15	152	15202	15202012012
15	152	15202	1	2	12	8394	16	3	4	98	98	98	98	98	0	0	15	152	15202	15202012012
15	152	15202	1	2	12	8394	17	3	2	98	98	98	98	98	0	0	15	152	15202	15202012012
15	152	15202	1	2	12	8394	18	3	2	98	98	98	98	98	0	0	15	152	15202	15202012012
15	152	15202	1	2	12	8394	19	3	1	99	99	99	99	99	1	1	15	152	15202	15202012012
15	152	15202	1	2	12	8394	20	3	1	5	3	5	3	99	1	1	15	152	15202	15202012012
15	152	15202	1	2	12	8394	21	3	1	5	99	5	1	4	1	2	15	152	15202	15202012012
15	152	15202	1	2	12	8394	22	3	2	98	98	98	98	98	0	0	15	152	15202	15202012012
15	152	15202	1	2	12	8394	23	3	4	98	98	98	98	98	0	0	15	152	15202	15202012012
15	152	15202	1	2	12	8394	24	3	1	5	3	5	1	2	1	2	15	152	15202	15202012012
15	152	15202	1	2	12	8394	25	3	4	98	98	98	98	98	0	0	15	152	15202	15202012012

Despleguemos los códigos de regiones de nuestra tabla:

regiones <- unique(tabla_con_clave$REGION)
regiones

##  [1] 15 14 13 12 11 10  9 16  8  7  6  5  4  3  2  1

Hagamos un subset con la 1:

tabla_con_clave <- filter(tabla_con_clave, tabla_con_clave$REGION == 4) 

1.2 Cálculo de frecuencias

tabla_con_clave_f <- tabla_con_clave[,-c(1,2,4,5,6,7,8,9,10,11,13,14,15,16,17,18,19,20),drop=FALSE] 
names(tabla_con_clave_f)[2] <- "Tipo de techo" 
# Ahora filtramos por Tipo de techo = 1.
tabla_con_clave_ff <- filter(tabla_con_clave_f, tabla_con_clave_f$`Tipo de techo` == 1)
# Determinamos las frecuencias por zona:
b <- tabla_con_clave_ff$clave
c <- tabla_con_clave_ff$`Tipo de techo`
d <- tabla_con_clave_ff$COMUNA
cross_tab =  xtabs( ~ unlist(b) + unlist(c)+ unlist(d))
tabla <- as.data.frame(cross_tab)
d <-tabla[!(tabla$Freq == 0),]
names(d)[1] <- "zona" 
d$anio <- "2017"

Veamos los primeros 100 registros:

r3_100 <- d[c(1:100),]
kbl(r3_100) %>%
  kable_styling(bootstrap_options = c("striped", "hover")) %>%
  kable_paper() %>%
  scroll_box(width = "100%", height = "300px")

zona	unlist.c.	unlist.d.	Freq	anio
4101011001	1	4101	119	2017
4101021001	1	4101	89	2017
4101021002	1	4101	108	2017
4101021003	1	4101	158	2017
4101021004	1	4101	222	2017
4101021005	1	4101	217	2017
4101022001	1	4101	85	2017
4101031001	1	4101	1023	2017
4101031002	1	4101	172	2017
4101031003	1	4101	670	2017
4101041001	1	4101	153	2017
4101041002	1	4101	89	2017
4101041003	1	4101	952	2017
4101041004	1	4101	452	2017
4101041005	1	4101	148	2017
4101041006	1	4101	130	2017
4101051001	1	4101	118	2017
4101051002	1	4101	216	2017
4101051003	1	4101	372	2017
4101051004	1	4101	286	2017
4101051005	1	4101	661	2017
4101051006	1	4101	1199	2017
4101051007	1	4101	560	2017
4101051008	1	4101	1047	2017
4101051009	1	4101	1119	2017
4101051010	1	4101	630	2017
4101051011	1	4101	712	2017
4101052007	1	4101	20	2017
4101061001	1	4101	253	2017
4101061002	1	4101	349	2017
4101061003	1	4101	679	2017
4101061004	1	4101	755	2017
4101061005	1	4101	35	2017
4101062001	1	4101	48	2017
4101062004	1	4101	114	2017
4101062006	1	4101	25	2017
4101062024	1	4101	15	2017
4101062030	1	4101	1	2017
4101062049	1	4101	25	2017
4101062901	1	4101	11	2017
4101071001	1	4101	35	2017
4101072002	1	4101	55	2017
4101072027	1	4101	17	2017
4101072029	1	4101	3	2017
4101072051	1	4101	20	2017
4101072053	1	4101	2	2017
4101072054	1	4101	4	2017
4101082011	1	4101	8	2017
4101082018	1	4101	25	2017
4101082021	1	4101	61	2017
4101082022	1	4101	1	2017
4101082023	1	4101	46	2017
4101082029	1	4101	7	2017
4101082043	1	4101	38	2017
4101082051	1	4101	5	2017
4101082052	1	4101	5	2017
4101082901	1	4101	6	2017
4101091001	1	4101	41	2017
4101092003	1	4101	94	2017
4101092034	1	4101	46	2017
4101092038	1	4101	6	2017
4101092039	1	4101	7	2017
4101092901	1	4101	2	2017
4101102003	1	4101	9	2017
4101102013	1	4101	49	2017
4101102015	1	4101	21	2017
4101102020	1	4101	169	2017
4101102032	1	4101	1	2017
4101122010	1	4101	1	2017
4101132025	1	4101	30	2017
4101132032	1	4101	19	2017
4101132046	1	4101	1	2017
4101132055	1	4101	1	2017
4101132901	1	4101	1	2017
4101141001	1	4101	154	2017
4101141002	1	4101	175	2017
4101141003	1	4101	378	2017
4101141004	1	4101	229	2017
4101141005	1	4101	510	2017
4101141006	1	4101	194	2017
4101142008	1	4101	6	2017
4101142012	1	4101	25	2017
4101142014	1	4101	23	2017
4101142019	1	4101	3	2017
4101142030	1	4101	2	2017
4101142033	1	4101	10	2017
4101142036	1	4101	4	2017
4101142040	1	4101	1	2017
4101142056	1	4101	98	2017
4101142057	1	4101	5	2017
4101142901	1	4101	36	2017
4101151001	1	4101	1228	2017
4101151002	1	4101	372	2017
4101151003	1	4101	391	2017
4101151004	1	4101	372	2017
4101151005	1	4101	506	2017
4101151006	1	4101	569	2017
4101161001	1	4101	241	2017
4101161002	1	4101	183	2017
4101161003	1	4101	130	2017

Agregamos un cero a los códigos comunales de cuatro dígitos:

codigos <- d$unlist.d.
rango <- seq(1:nrow(d))
cadena <- paste("0",codigos[rango], sep = "")
cadena <- substr(cadena,(nchar(cadena)[rango])-(4),6)
codigos <- as.data.frame(codigos)
cadena <- as.data.frame(cadena)
comuna_corr <- cbind(d,cadena)
comuna_corr <- comuna_corr[,-c(2,3),drop=FALSE]
names(comuna_corr)[4] <- "código" 
r3_100 <- comuna_corr[c(1:100),]
kbl(r3_100) %>%
  kable_styling(bootstrap_options = c("striped", "hover")) %>%
  kable_paper() %>%
  scroll_box(width = "100%", height = "300px")

zona	Freq	anio	código
4101011001	119	2017	04101
4101021001	89	2017	04101
4101021002	108	2017	04101
4101021003	158	2017	04101
4101021004	222	2017	04101
4101021005	217	2017	04101
4101022001	85	2017	04101
4101031001	1023	2017	04101
4101031002	172	2017	04101
4101031003	670	2017	04101
4101041001	153	2017	04101
4101041002	89	2017	04101
4101041003	952	2017	04101
4101041004	452	2017	04101
4101041005	148	2017	04101
4101041006	130	2017	04101
4101051001	118	2017	04101
4101051002	216	2017	04101
4101051003	372	2017	04101
4101051004	286	2017	04101
4101051005	661	2017	04101
4101051006	1199	2017	04101
4101051007	560	2017	04101
4101051008	1047	2017	04101
4101051009	1119	2017	04101
4101051010	630	2017	04101
4101051011	712	2017	04101
4101052007	20	2017	04101
4101061001	253	2017	04101
4101061002	349	2017	04101
4101061003	679	2017	04101
4101061004	755	2017	04101
4101061005	35	2017	04101
4101062001	48	2017	04101
4101062004	114	2017	04101
4101062006	25	2017	04101
4101062024	15	2017	04101
4101062030	1	2017	04101
4101062049	25	2017	04101
4101062901	11	2017	04101
4101071001	35	2017	04101
4101072002	55	2017	04101
4101072027	17	2017	04101
4101072029	3	2017	04101
4101072051	20	2017	04101
4101072053	2	2017	04101
4101072054	4	2017	04101
4101082011	8	2017	04101
4101082018	25	2017	04101
4101082021	61	2017	04101
4101082022	1	2017	04101
4101082023	46	2017	04101
4101082029	7	2017	04101
4101082043	38	2017	04101
4101082051	5	2017	04101
4101082052	5	2017	04101
4101082901	6	2017	04101
4101091001	41	2017	04101
4101092003	94	2017	04101
4101092034	46	2017	04101
4101092038	6	2017	04101
4101092039	7	2017	04101
4101092901	2	2017	04101
4101102003	9	2017	04101
4101102013	49	2017	04101
4101102015	21	2017	04101
4101102020	169	2017	04101
4101102032	1	2017	04101
4101122010	1	2017	04101
4101132025	30	2017	04101
4101132032	19	2017	04101
4101132046	1	2017	04101
4101132055	1	2017	04101
4101132901	1	2017	04101
4101141001	154	2017	04101
4101141002	175	2017	04101
4101141003	378	2017	04101
4101141004	229	2017	04101
4101141005	510	2017	04101
4101141006	194	2017	04101
4101142008	6	2017	04101
4101142012	25	2017	04101
4101142014	23	2017	04101
4101142019	3	2017	04101
4101142030	2	2017	04101
4101142033	10	2017	04101
4101142036	4	2017	04101
4101142040	1	2017	04101
4101142056	98	2017	04101
4101142057	5	2017	04101
4101142901	36	2017	04101
4101151001	1228	2017	04101
4101151002	372	2017	04101
4101151003	391	2017	04101
4101151004	372	2017	04101
4101151005	506	2017	04101
4101151006	569	2017	04101
4101161001	241	2017	04101
4101161002	183	2017	04101
4101161003	130	2017	04101

2 Variable CASEN

2.1 Tabla de ingresos expandidos

Hemos calculado ya éste valor como conclusión del punto 1.1 de aquí

h_y_m_2017_censo <- readRDS("ingresos_expandidos_17.rds")
tablamadre <- head(h_y_m_2017_censo,50)
kbl(tablamadre) %>%
  kable_styling(bootstrap_options = c("striped", "hover")) %>%
  kable_paper() %>%
  scroll_box(width = "100%", height = "300px")

código	comuna.x	promedio_i	año	comuna.y	personas	Ingresos_expandidos
01101	Iquique	354820.7	2017	1101	191468	67936815240
01107	Alto Hospicio	301933.4	2017	1107	108375	32722034397
01401	Pozo Almonte	285981.8	2017	1401	15711	4493059532
01402	Camiña	262850.3	2017	1402	1250	328562901
01404	Huara	253968.5	2017	1404	2730	693334131
01405	Pica	313007.5	2017	1405	9296	2909717399
02101	Antofagasta	347580.2	2017	2101	361873	125779893517
02102	Mejillones	369770.7	2017	2102	13467	4979702302
02103	Sierra Gorda	403458.5	2017	2103	10186	4109628188
02104	Taltal	364539.1	2017	2104	13317	4854566842
02201	Calama	409671.3	2017	2201	165731	67895226712
02203	San Pedro de Atacama	426592.0	2017	2203	10996	4690805471
02301	Tocopilla	246615.3	2017	2301	25186	6211253937
02302	María Elena	466266.9	2017	2302	6457	3010685220
03101	Copiapó	330075.2	2017	3101	153937	50810778473
03102	Caldera	299314.8	2017	3102	17662	5286498241
03103	Tierra Amarilla	314643.9	2017	3103	14019	4410992711
03201	Chañaral	286389.3	2017	3201	12219	3499391196
03202	Diego de Almagro	336256.8	2017	3202	13925	4682376047
03301	Vallenar	304336.7	2017	3301	51917	15800246795
03302	Alto del Carmen	227130.4	2017	3302	5299	1203563833
03303	Freirina	253086.7	2017	3303	7041	1781983257
03304	Huasco	287406.6	2017	3304	10149	2916889629
04101	La Serena	270221.9	2017	4101	221054	59733627577
04102	Coquimbo	261852.6	2017	4102	227730	59631700074
04103	Andacollo	248209.3	2017	4103	11044	2741223967
04104	La Higuera	228356.8	2017	4104	4241	968461330
04105	Paiguano	205942.1	2017	4105	4497	926121774
04106	Vicuña	211431.9	2017	4106	27771	5871675449
04201	Illapel	238674.4	2017	4201	30848	7362627007
04202	Canela	207933.6	2017	4202	9093	1890740321
04203	Los Vilos	255200.4	2017	4203	21382	5456695139
04204	Salamanca	242879.5	2017	4204	29347	7127783272
04301	Ovalle	266522.9	2017	4301	111272	29656533187
04302	Combarbalá	210409.7	2017	4302	13322	2803077721
04303	Monte Patria	211907.9	2017	4303	30751	6516380780
04304	Punitaqui	194997.8	2017	4304	10956	2136395349
04305	Río Hurtado	182027.2	2017	4305	4278	778712384
05101	Valparaíso	298720.7	2017	5101	296655	88616992249
05102	Casablanca	312802.7	2017	5102	26867	8404070481
05103	Concón	318496.3	2017	5103	42152	13425257057
05105	Puchuncaví	288737.2	2017	5105	18546	5354920887
05107	Quintero	316659.1	2017	5107	31923	10108709691
05109	Viña del Mar	337006.1	2017	5109	334248	112643604611
05301	Los Andes	338182.5	2017	5301	66708	22559476922
05302	Calle Larga	245165.4	2017	5302	14832	3636293159
05303	Rinconada	281633.2	2017	5303	10207	2874630315
05304	San Esteban	220958.4	2017	5304	18855	4166170587
05401	La Ligua	229623.7	2017	5401	35390	8126381563
05402	Cabildo	249717.7	2017	5402	19388	4841527150

3 Unión Censo-Casen

Integramos a la tabla censal de frecuencias la tabla de ingresos expandidos de la Casen.

comunas_con_ing_exp = merge( x = comuna_corr, y = h_y_m_2017_censo, by = "código", all.x = TRUE)
r3_100 <- comunas_con_ing_exp[c(1:100),]
kbl(r3_100) %>%
  kable_styling(bootstrap_options = c("striped", "hover")) %>%
  kable_paper() %>%
  scroll_box(width = "100%", height = "300px")

código	zona	Freq	anio	comuna.x	promedio_i	año	comuna.y	personas	Ingresos_expandidos
04101	4101011001	119	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101021001	89	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101021002	108	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101021003	158	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101021004	222	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101021005	217	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101022001	85	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101031001	1023	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101031002	172	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101031003	670	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101041001	153	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101041002	89	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101041003	952	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101041004	452	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101041005	148	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101041006	130	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101051001	118	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101051002	216	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101051003	372	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101051004	286	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101051005	661	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101051006	1199	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101051007	560	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101051008	1047	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101051009	1119	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101051010	630	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101051011	712	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101052007	20	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101061001	253	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101061002	349	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101061003	679	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101061004	755	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101061005	35	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101062001	48	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101062004	114	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101062006	25	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101062024	15	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101062030	1	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101062049	25	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101062901	11	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101071001	35	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101072002	55	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101072027	17	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101072029	3	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101072051	20	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101072053	2	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101072054	4	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101082011	8	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101082018	25	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101082021	61	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101082022	1	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101082023	46	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101082029	7	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101082043	38	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101082051	5	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101082052	5	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101082901	6	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101091001	41	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101092003	94	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101092034	46	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101092038	6	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101092039	7	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101092901	2	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101102003	9	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101102013	49	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101102015	21	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101102020	169	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101102032	1	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101122010	1	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101132025	30	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101132032	19	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101132046	1	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101132055	1	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101132901	1	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101141001	154	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101141002	175	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101141003	378	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101141004	229	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101141005	510	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101141006	194	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101142008	6	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101142012	25	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101142014	23	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101142019	3	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101142030	2	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101142033	10	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101142036	4	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101142040	1	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101142056	98	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101142057	5	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101142901	36	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101151001	1228	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101151002	372	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101151003	391	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101151004	372	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101151005	506	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101151006	569	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101161001	241	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101161002	183	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101161003	130	2017	La Serena	270221.9	2017	4101	221054	59733627577

4 Proporción poblacional zonal respecto a la comunal

Del censo obtenemos la cantidad de población a nivel de zona y estimamos su proporción a nivel comunal. Ya hemos calculado ésta proporción aquí.

prop_pob <- readRDS("tabla_de_prop_pob.rds")
names(prop_pob)[1] <- "zona"
names(prop_pob)[3] <- "p_poblacional" 

Veamos los 100 primeros registros:

r3_100 <- prop_pob[c(1:100),]
kbl(r3_100) %>%
  kable_styling(bootstrap_options = c("striped", "hover")) %>%
  kable_paper() %>%
  scroll_box(width = "100%", height = "300px")

zona	Freq	p_poblacional	código
1101011001	2491	0.0130100	01101
1101011002	1475	0.0077036	01101
1101021001	1003	0.0052385	01101
1101021002	54	0.0002820	01101
1101021003	2895	0.0151200	01101
1101021004	2398	0.0125243	01101
1101021005	4525	0.0236332	01101
1101031001	2725	0.0142321	01101
1101031002	3554	0.0185618	01101
1101031003	5246	0.0273988	01101
1101031004	3389	0.0177001	01101
1101041001	1800	0.0094010	01101
1101041002	2538	0.0132555	01101
1101041003	3855	0.0201339	01101
1101041004	5663	0.0295767	01101
1101041005	4162	0.0217373	01101
1101041006	2689	0.0140441	01101
1101051001	3296	0.0172144	01101
1101051002	4465	0.0233198	01101
1101051003	4656	0.0243174	01101
1101051004	2097	0.0109522	01101
1101051005	3569	0.0186402	01101
1101051006	2741	0.0143157	01101
1101061001	1625	0.0084871	01101
1101061002	4767	0.0248971	01101
1101061003	4826	0.0252053	01101
1101061004	4077	0.0212934	01101
1101061005	2166	0.0113126	01101
1101071001	2324	0.0121378	01101
1101071002	2801	0.0146291	01101
1101071003	3829	0.0199981	01101
1101071004	1987	0.0103777	01101
1101081001	5133	0.0268087	01101
1101081002	3233	0.0168853	01101
1101081003	2122	0.0110828	01101
1101081004	2392	0.0124929	01101
1101092001	57	0.0002977	01101
1101092004	247	0.0012900	01101
1101092005	76	0.0003969	01101
1101092006	603	0.0031494	01101
1101092007	84	0.0004387	01101
1101092010	398	0.0020787	01101
1101092012	58	0.0003029	01101
1101092014	23	0.0001201	01101
1101092016	20	0.0001045	01101
1101092017	8	0.0000418	01101
1101092018	74	0.0003865	01101
1101092019	25	0.0001306	01101
1101092021	177	0.0009244	01101
1101092022	23	0.0001201	01101
1101092023	288	0.0015042	01101
1101092024	14	0.0000731	01101
1101092901	30	0.0001567	01101
1101101001	2672	0.0139553	01101
1101101002	4398	0.0229699	01101
1101101003	4524	0.0236280	01101
1101101004	3544	0.0185096	01101
1101101005	4911	0.0256492	01101
1101101006	3688	0.0192617	01101
1101111001	3886	0.0202958	01101
1101111002	2312	0.0120751	01101
1101111003	4874	0.0254560	01101
1101111004	4543	0.0237272	01101
1101111005	4331	0.0226200	01101
1101111006	3253	0.0169898	01101
1101111007	4639	0.0242286	01101
1101111008	4881	0.0254925	01101
1101111009	5006	0.0261454	01101
1101111010	366	0.0019115	01101
1101111011	4351	0.0227244	01101
1101111012	2926	0.0152819	01101
1101111013	3390	0.0177053	01101
1101111014	2940	0.0153550	01101
1101112003	33	0.0001724	01101
1101112013	104	0.0005432	01101
1101112019	34	0.0001776	01101
1101112025	21	0.0001097	01101
1101112901	6	0.0000313	01101
1101991999	1062	0.0055466	01101
1107011001	4104	0.0378685	01107
1107011002	4360	0.0402307	01107
1107011003	8549	0.0788835	01107
1107012003	3	0.0000277	01107
1107012901	17	0.0001569	01107
1107021001	6701	0.0618316	01107
1107021002	3971	0.0366413	01107
1107021003	6349	0.0585836	01107
1107021004	5125	0.0472895	01107
1107021005	4451	0.0410704	01107
1107021006	3864	0.0356540	01107
1107021007	5235	0.0483045	01107
1107021008	4566	0.0421315	01107
1107031001	4195	0.0387082	01107
1107031002	7099	0.0655040	01107
1107031003	4720	0.0435525	01107
1107032005	38	0.0003506	01107
1107032006	2399	0.0221361	01107
1107032008	4	0.0000369	01107
1107041001	3630	0.0334948	01107
1107041002	5358	0.0494394	01107

5 Ingreso medio

Deseamos el valor del ingreso promedio a nivel comunal, pero expandido a nivel zonal. Ésta información está contenida en el campo promedio_i de la tabla obtenida en el punto 3.

r3_100 <- comunas_con_ing_exp[c(1:100),]
kbl(r3_100) %>%
  kable_styling(bootstrap_options = c("striped", "hover")) %>%
  kable_paper() %>%
  scroll_box(width = "100%", height = "300px")

código	zona	Freq	anio	comuna.x	promedio_i	año	comuna.y	personas	Ingresos_expandidos
04101	4101011001	119	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101021001	89	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101021002	108	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101021003	158	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101021004	222	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101021005	217	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101022001	85	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101031001	1023	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101031002	172	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101031003	670	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101041001	153	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101041002	89	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101041003	952	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101041004	452	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101041005	148	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101041006	130	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101051001	118	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101051002	216	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101051003	372	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101051004	286	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101051005	661	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101051006	1199	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101051007	560	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101051008	1047	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101051009	1119	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101051010	630	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101051011	712	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101052007	20	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101061001	253	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101061002	349	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101061003	679	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101061004	755	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101061005	35	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101062001	48	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101062004	114	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101062006	25	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101062024	15	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101062030	1	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101062049	25	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101062901	11	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101071001	35	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101072002	55	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101072027	17	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101072029	3	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101072051	20	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101072053	2	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101072054	4	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101082011	8	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101082018	25	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101082021	61	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101082022	1	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101082023	46	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101082029	7	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101082043	38	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101082051	5	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101082052	5	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101082901	6	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101091001	41	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101092003	94	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101092034	46	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101092038	6	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101092039	7	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101092901	2	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101102003	9	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101102013	49	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101102015	21	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101102020	169	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101102032	1	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101122010	1	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101132025	30	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101132032	19	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101132046	1	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101132055	1	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101132901	1	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101141001	154	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101141002	175	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101141003	378	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101141004	229	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101141005	510	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101141006	194	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101142008	6	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101142012	25	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101142014	23	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101142019	3	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101142030	2	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101142033	10	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101142036	4	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101142040	1	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101142056	98	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101142057	5	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101142901	36	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101151001	1228	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101151002	372	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101151003	391	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101151004	372	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101151005	506	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101151006	569	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101161001	241	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101161002	183	2017	La Serena	270221.9	2017	4101	221054	59733627577
04101	4101161003	130	2017	La Serena	270221.9	2017	4101	221054	59733627577

6 Ingreso promedio expandido por zona (multi_pob)

En éste momento vamos a construir nuestra variable dependiente de regresión aplicando la siguiente fórmula:

\[ multi\_pob = promedio\_i \cdot personas \cdot p\_poblacional \]

Para ello integramos a la tabla de ingresos expandidos a nivel zonal (punto 3) la tabla de proporciones poblacionales zonales respecto al total comunal (punto 4) :

h_y_m_comuna_corr_01 = merge( x = comunas_con_ing_exp, y = prop_pob, by = "zona", all.x = TRUE)
tablamadre <- head(h_y_m_comuna_corr_01,100)
kbl(tablamadre) %>%
  kable_styling(bootstrap_options = c("striped", "hover")) %>%
  kable_paper() %>%
  scroll_box(width = "100%", height = "300px")

zona	código.x	Freq.x	anio	comuna.x	promedio_i	año	comuna.y	personas	Ingresos_expandidos	Freq.y	p_poblacional	código.y
4101011001	04101	119	2017	La Serena	270221.9	2017	4101	221054	59733627577	1455	0.0065821	04101
4101021001	04101	89	2017	La Serena	270221.9	2017	4101	221054	59733627577	2431	0.0109973	04101
4101021002	04101	108	2017	La Serena	270221.9	2017	4101	221054	59733627577	2926	0.0132366	04101
4101021003	04101	158	2017	La Serena	270221.9	2017	4101	221054	59733627577	2699	0.0122097	04101
4101021004	04101	222	2017	La Serena	270221.9	2017	4101	221054	59733627577	5323	0.0240801	04101
4101021005	04101	217	2017	La Serena	270221.9	2017	4101	221054	59733627577	2125	0.0096130	04101
4101022001	04101	85	2017	La Serena	270221.9	2017	4101	221054	59733627577	1157	0.0052340	04101
4101031001	04101	1023	2017	La Serena	270221.9	2017	4101	221054	59733627577	4341	0.0196377	04101
4101031002	04101	172	2017	La Serena	270221.9	2017	4101	221054	59733627577	2583	0.0116849	04101
4101031003	04101	670	2017	La Serena	270221.9	2017	4101	221054	59733627577	4026	0.0182127	04101
4101041001	04101	153	2017	La Serena	270221.9	2017	4101	221054	59733627577	1108	0.0050123	04101
4101041002	04101	89	2017	La Serena	270221.9	2017	4101	221054	59733627577	1015	0.0045916	04101
4101041003	04101	952	2017	La Serena	270221.9	2017	4101	221054	59733627577	4721	0.0213568	04101
4101041004	04101	452	2017	La Serena	270221.9	2017	4101	221054	59733627577	3560	0.0161047	04101
4101041005	04101	148	2017	La Serena	270221.9	2017	4101	221054	59733627577	812	0.0036733	04101
4101041006	04101	130	2017	La Serena	270221.9	2017	4101	221054	59733627577	821	0.0037140	04101
4101051001	04101	118	2017	La Serena	270221.9	2017	4101	221054	59733627577	1419	0.0064192	04101
4101051002	04101	216	2017	La Serena	270221.9	2017	4101	221054	59733627577	2920	0.0132094	04101
4101051003	04101	372	2017	La Serena	270221.9	2017	4101	221054	59733627577	3348	0.0151456	04101
4101051004	04101	286	2017	La Serena	270221.9	2017	4101	221054	59733627577	2851	0.0128973	04101
4101051005	04101	661	2017	La Serena	270221.9	2017	4101	221054	59733627577	5493	0.0248491	04101
4101051006	04101	1199	2017	La Serena	270221.9	2017	4101	221054	59733627577	4295	0.0194296	04101
4101051007	04101	560	2017	La Serena	270221.9	2017	4101	221054	59733627577	2336	0.0105676	04101
4101051008	04101	1047	2017	La Serena	270221.9	2017	4101	221054	59733627577	4235	0.0191582	04101
4101051009	04101	1119	2017	La Serena	270221.9	2017	4101	221054	59733627577	3882	0.0175613	04101
4101051010	04101	630	2017	La Serena	270221.9	2017	4101	221054	59733627577	3226	0.0145937	04101
4101051011	04101	712	2017	La Serena	270221.9	2017	4101	221054	59733627577	2966	0.0134175	04101
4101052007	04101	20	2017	La Serena	270221.9	2017	4101	221054	59733627577	125	0.0005655	04101
4101061001	04101	253	2017	La Serena	270221.9	2017	4101	221054	59733627577	4424	0.0200132	04101
4101061002	04101	349	2017	La Serena	270221.9	2017	4101	221054	59733627577	3047	0.0137840	04101
4101061003	04101	679	2017	La Serena	270221.9	2017	4101	221054	59733627577	3472	0.0157066	04101
4101061004	04101	755	2017	La Serena	270221.9	2017	4101	221054	59733627577	5333	0.0241253	04101
4101061005	04101	35	2017	La Serena	270221.9	2017	4101	221054	59733627577	288	0.0013028	04101
4101062001	04101	48	2017	La Serena	270221.9	2017	4101	221054	59733627577	345	0.0015607	04101
4101062004	04101	114	2017	La Serena	270221.9	2017	4101	221054	59733627577	740	0.0033476	04101
4101062006	04101	25	2017	La Serena	270221.9	2017	4101	221054	59733627577	224	0.0010133	04101
4101062024	04101	15	2017	La Serena	270221.9	2017	4101	221054	59733627577	2392	0.0108209	04101
4101062030	04101	1	2017	La Serena	270221.9	2017	4101	221054	59733627577	41	0.0001855	04101
4101062049	04101	25	2017	La Serena	270221.9	2017	4101	221054	59733627577	115	0.0005202	04101
4101062901	04101	11	2017	La Serena	270221.9	2017	4101	221054	59733627577	284	0.0012848	04101
4101071001	04101	35	2017	La Serena	270221.9	2017	4101	221054	59733627577	1056	0.0047771	04101
4101072002	04101	55	2017	La Serena	270221.9	2017	4101	221054	59733627577	394	0.0017824	04101
4101072027	04101	17	2017	La Serena	270221.9	2017	4101	221054	59733627577	461	0.0020855	04101
4101072029	04101	3	2017	La Serena	270221.9	2017	4101	221054	59733627577	119	0.0005383	04101
4101072051	04101	20	2017	La Serena	270221.9	2017	4101	221054	59733627577	179	0.0008098	04101
4101072053	04101	2	2017	La Serena	270221.9	2017	4101	221054	59733627577	35	0.0001583	04101
4101072054	04101	4	2017	La Serena	270221.9	2017	4101	221054	59733627577	114	0.0005157	04101
4101082011	04101	8	2017	La Serena	270221.9	2017	4101	221054	59733627577	304	0.0013752	04101
4101082018	04101	25	2017	La Serena	270221.9	2017	4101	221054	59733627577	348	0.0015743	04101
4101082021	04101	61	2017	La Serena	270221.9	2017	4101	221054	59733627577	748	0.0033838	04101
4101082022	04101	1	2017	La Serena	270221.9	2017	4101	221054	59733627577	13	0.0000588	04101
4101082023	04101	46	2017	La Serena	270221.9	2017	4101	221054	59733627577	733	0.0033159	04101
4101082029	04101	7	2017	La Serena	270221.9	2017	4101	221054	59733627577	140	0.0006333	04101
4101082043	04101	38	2017	La Serena	270221.9	2017	4101	221054	59733627577	692	0.0031305	04101
4101082051	04101	5	2017	La Serena	270221.9	2017	4101	221054	59733627577	36	0.0001629	04101
4101082052	04101	5	2017	La Serena	270221.9	2017	4101	221054	59733627577	52	0.0002352	04101
4101082901	04101	6	2017	La Serena	270221.9	2017	4101	221054	59733627577	37	0.0001674	04101
4101091001	04101	41	2017	La Serena	270221.9	2017	4101	221054	59733627577	1292	0.0058447	04101
4101092003	04101	94	2017	La Serena	270221.9	2017	4101	221054	59733627577	740	0.0033476	04101
4101092034	04101	46	2017	La Serena	270221.9	2017	4101	221054	59733627577	742	0.0033566	04101
4101092038	04101	6	2017	La Serena	270221.9	2017	4101	221054	59733627577	329	0.0014883	04101
4101092039	04101	7	2017	La Serena	270221.9	2017	4101	221054	59733627577	63	0.0002850	04101
4101092901	04101	2	2017	La Serena	270221.9	2017	4101	221054	59733627577	60	0.0002714	04101
4101102003	04101	9	2017	La Serena	270221.9	2017	4101	221054	59733627577	70	0.0003167	04101
4101102013	04101	49	2017	La Serena	270221.9	2017	4101	221054	59733627577	1201	0.0054331	04101
4101102015	04101	21	2017	La Serena	270221.9	2017	4101	221054	59733627577	364	0.0016467	04101
4101102020	04101	169	2017	La Serena	270221.9	2017	4101	221054	59733627577	2212	0.0100066	04101
4101102032	04101	1	2017	La Serena	270221.9	2017	4101	221054	59733627577	48	0.0002171	04101
4101122010	04101	1	2017	La Serena	270221.9	2017	4101	221054	59733627577	44	0.0001990	04101
4101132025	04101	30	2017	La Serena	270221.9	2017	4101	221054	59733627577	987	0.0044650	04101
4101132032	04101	19	2017	La Serena	270221.9	2017	4101	221054	59733627577	824	0.0037276	04101
4101132046	04101	1	2017	La Serena	270221.9	2017	4101	221054	59733627577	23	0.0001040	04101
4101132055	04101	1	2017	La Serena	270221.9	2017	4101	221054	59733627577	23	0.0001040	04101
4101132901	04101	1	2017	La Serena	270221.9	2017	4101	221054	59733627577	36	0.0001629	04101
4101141001	04101	154	2017	La Serena	270221.9	2017	4101	221054	59733627577	2872	0.0129923	04101
4101141002	04101	175	2017	La Serena	270221.9	2017	4101	221054	59733627577	2750	0.0124404	04101
4101141003	04101	378	2017	La Serena	270221.9	2017	4101	221054	59733627577	4706	0.0212889	04101
4101141004	04101	229	2017	La Serena	270221.9	2017	4101	221054	59733627577	3750	0.0169642	04101
4101141005	04101	510	2017	La Serena	270221.9	2017	4101	221054	59733627577	5866	0.0265365	04101
4101141006	04101	194	2017	La Serena	270221.9	2017	4101	221054	59733627577	2114	0.0095633	04101
4101142008	04101	6	2017	La Serena	270221.9	2017	4101	221054	59733627577	95	0.0004298	04101
4101142012	04101	25	2017	La Serena	270221.9	2017	4101	221054	59733627577	175	0.0007917	04101
4101142014	04101	23	2017	La Serena	270221.9	2017	4101	221054	59733627577	519	0.0023478	04101
4101142019	04101	3	2017	La Serena	270221.9	2017	4101	221054	59733627577	194	0.0008776	04101
4101142030	04101	2	2017	La Serena	270221.9	2017	4101	221054	59733627577	147	0.0006650	04101
4101142033	04101	10	2017	La Serena	270221.9	2017	4101	221054	59733627577	51	0.0002307	04101
4101142036	04101	4	2017	La Serena	270221.9	2017	4101	221054	59733627577	225	0.0010179	04101
4101142040	04101	1	2017	La Serena	270221.9	2017	4101	221054	59733627577	92	0.0004162	04101
4101142056	04101	98	2017	La Serena	270221.9	2017	4101	221054	59733627577	383	0.0017326	04101
4101142057	04101	5	2017	La Serena	270221.9	2017	4101	221054	59733627577	45	0.0002036	04101
4101142901	04101	36	2017	La Serena	270221.9	2017	4101	221054	59733627577	324	0.0014657	04101
4101151001	04101	1228	2017	La Serena	270221.9	2017	4101	221054	59733627577	4957	0.0224244	04101
4101151002	04101	372	2017	La Serena	270221.9	2017	4101	221054	59733627577	1602	0.0072471	04101
4101151003	04101	391	2017	La Serena	270221.9	2017	4101	221054	59733627577	1900	0.0085952	04101
4101151004	04101	372	2017	La Serena	270221.9	2017	4101	221054	59733627577	2649	0.0119835	04101
4101151005	04101	506	2017	La Serena	270221.9	2017	4101	221054	59733627577	2047	0.0092602	04101
4101151006	04101	569	2017	La Serena	270221.9	2017	4101	221054	59733627577	3173	0.0143540	04101
4101161001	04101	241	2017	La Serena	270221.9	2017	4101	221054	59733627577	5756	0.0260389	04101
4101161002	04101	183	2017	La Serena	270221.9	2017	4101	221054	59733627577	3690	0.0166928	04101
4101161003	04101	130	2017	La Serena	270221.9	2017	4101	221054	59733627577	2952	0.0133542	04101

Hacemos la multiplicación que queda almacenada en la variable multi_pob:

h_y_m_comuna_corr_01$multi_pob <- h_y_m_comuna_corr_01$promedio_i * h_y_m_comuna_corr_01$personas * h_y_m_comuna_corr_01$p_poblacional
tablamadre <- head(h_y_m_comuna_corr_01,100)
kbl(tablamadre) %>%
  kable_styling(bootstrap_options = c("striped", "hover")) %>%
  kable_paper() %>%
  scroll_box(width = "100%", height = "300px")

zona	código.x	Freq.x	anio	comuna.x	promedio_i	año	comuna.y	personas	Ingresos_expandidos	Freq.y	p_poblacional	código.y	multi_pob
4101011001	04101	119	2017	La Serena	270221.9	2017	4101	221054	59733627577	1455	0.0065821	04101	393172836
4101021001	04101	89	2017	La Serena	270221.9	2017	4101	221054	59733627577	2431	0.0109973	04101	656909392
4101021002	04101	108	2017	La Serena	270221.9	2017	4101	221054	59733627577	2926	0.0132366	04101	790669222
4101021003	04101	158	2017	La Serena	270221.9	2017	4101	221054	59733627577	2699	0.0122097	04101	729328856
4101021004	04101	222	2017	La Serena	270221.9	2017	4101	221054	59733627577	5323	0.0240801	04101	1438391070
4101021005	04101	217	2017	La Serena	270221.9	2017	4101	221054	59733627577	2125	0.0096130	04101	574221496
4101022001	04101	85	2017	La Serena	270221.9	2017	4101	221054	59733627577	1157	0.0052340	04101	312646716
4101031001	04101	1023	2017	La Serena	270221.9	2017	4101	221054	59733627577	4341	0.0196377	04101	1173033183
4101031002	04101	172	2017	La Serena	270221.9	2017	4101	221054	59733627577	2583	0.0116849	04101	697983117
4101031003	04101	670	2017	La Serena	270221.9	2017	4101	221054	59733627577	4026	0.0182127	04101	1087913291
4101041001	04101	153	2017	La Serena	270221.9	2017	4101	221054	59733627577	1108	0.0050123	04101	299405844
4101041002	04101	89	2017	La Serena	270221.9	2017	4101	221054	59733627577	1015	0.0045916	04101	274275209
4101041003	04101	952	2017	La Serena	270221.9	2017	4101	221054	59733627577	4721	0.0213568	04101	1275717498
4101041004	04101	452	2017	La Serena	270221.9	2017	4101	221054	59733627577	3560	0.0161047	04101	961989895
4101041005	04101	148	2017	La Serena	270221.9	2017	4101	221054	59733627577	812	0.0036733	04101	219420167
4101041006	04101	130	2017	La Serena	270221.9	2017	4101	221054	59733627577	821	0.0037140	04101	221852164
4101051001	04101	118	2017	La Serena	270221.9	2017	4101	221054	59733627577	1419	0.0064192	04101	383444848
4101051002	04101	216	2017	La Serena	270221.9	2017	4101	221054	59733627577	2920	0.0132094	04101	789047891
4101051003	04101	372	2017	La Serena	270221.9	2017	4101	221054	59733627577	3348	0.0151456	04101	904702856
4101051004	04101	286	2017	La Serena	270221.9	2017	4101	221054	59733627577	2851	0.0128973	04101	770402581
4101051005	04101	661	2017	La Serena	270221.9	2017	4101	221054	59733627577	5493	0.0248491	04101	1484328790
4101051006	04101	1199	2017	La Serena	270221.9	2017	4101	221054	59733627577	4295	0.0194296	04101	1160602977
4101051007	04101	560	2017	La Serena	270221.9	2017	4101	221054	59733627577	2336	0.0105676	04101	631238313
4101051008	04101	1047	2017	La Serena	270221.9	2017	4101	221054	59733627577	4235	0.0191582	04101	1144389664
4101051009	04101	1119	2017	La Serena	270221.9	2017	4101	221054	59733627577	3882	0.0175613	04101	1049001340
4101051010	04101	630	2017	La Serena	270221.9	2017	4101	221054	59733627577	3226	0.0145937	04101	871735787
4101051011	04101	712	2017	La Serena	270221.9	2017	4101	221054	59733627577	2966	0.0134175	04101	801478098
4101052007	04101	20	2017	La Serena	270221.9	2017	4101	221054	59733627577	125	0.0005655	04101	33777735
4101061001	04101	253	2017	La Serena	270221.9	2017	4101	221054	59733627577	4424	0.0200132	04101	1195461599
4101061002	04101	349	2017	La Serena	270221.9	2017	4101	221054	59733627577	3047	0.0137840	04101	823366070
4101061003	04101	679	2017	La Serena	270221.9	2017	4101	221054	59733627577	3472	0.0157066	04101	938210369
4101061004	04101	755	2017	La Serena	270221.9	2017	4101	221054	59733627577	5333	0.0241253	04101	1441093289
4101061005	04101	35	2017	La Serena	270221.9	2017	4101	221054	59733627577	288	0.0013028	04101	77823902
4101062001	04101	48	2017	La Serena	270221.9	2017	4101	221054	59733627577	345	0.0015607	04101	93226549
4101062004	04101	114	2017	La Serena	270221.9	2017	4101	221054	59733627577	740	0.0033476	04101	199964192
4101062006	04101	25	2017	La Serena	270221.9	2017	4101	221054	59733627577	224	0.0010133	04101	60529701
4101062024	04101	15	2017	La Serena	270221.9	2017	4101	221054	59733627577	2392	0.0108209	04101	646370738
4101062030	04101	1	2017	La Serena	270221.9	2017	4101	221054	59733627577	41	0.0001855	04101	11079097
4101062049	04101	25	2017	La Serena	270221.9	2017	4101	221054	59733627577	115	0.0005202	04101	31075516
4101062901	04101	11	2017	La Serena	270221.9	2017	4101	221054	59733627577	284	0.0012848	04101	76743014
4101071001	04101	35	2017	La Serena	270221.9	2017	4101	221054	59733627577	1056	0.0047771	04101	285354306
4101072002	04101	55	2017	La Serena	270221.9	2017	4101	221054	59733627577	394	0.0017824	04101	106467421
4101072027	04101	17	2017	La Serena	270221.9	2017	4101	221054	59733627577	461	0.0020855	04101	124572287
4101072029	04101	3	2017	La Serena	270221.9	2017	4101	221054	59733627577	119	0.0005383	04101	32156404
4101072051	04101	20	2017	La Serena	270221.9	2017	4101	221054	59733627577	179	0.0008098	04101	48369717
4101072053	04101	2	2017	La Serena	270221.9	2017	4101	221054	59733627577	35	0.0001583	04101	9457766
4101072054	04101	4	2017	La Serena	270221.9	2017	4101	221054	59733627577	114	0.0005157	04101	30805294
4101082011	04101	8	2017	La Serena	270221.9	2017	4101	221054	59733627577	304	0.0013752	04101	82147452
4101082018	04101	25	2017	La Serena	270221.9	2017	4101	221054	59733627577	348	0.0015743	04101	94037214
4101082021	04101	61	2017	La Serena	270221.9	2017	4101	221054	59733627577	748	0.0033838	04101	202125967
4101082022	04101	1	2017	La Serena	270221.9	2017	4101	221054	59733627577	13	0.0000588	04101	3512884
4101082023	04101	46	2017	La Serena	270221.9	2017	4101	221054	59733627577	733	0.0033159	04101	198072638
4101082029	04101	7	2017	La Serena	270221.9	2017	4101	221054	59733627577	140	0.0006333	04101	37831063
4101082043	04101	38	2017	La Serena	270221.9	2017	4101	221054	59733627577	692	0.0031305	04101	186993541
4101082051	04101	5	2017	La Serena	270221.9	2017	4101	221054	59733627577	36	0.0001629	04101	9727988
4101082052	04101	5	2017	La Serena	270221.9	2017	4101	221054	59733627577	52	0.0002352	04101	14051538
4101082901	04101	6	2017	La Serena	270221.9	2017	4101	221054	59733627577	37	0.0001674	04101	9998210
4101091001	04101	41	2017	La Serena	270221.9	2017	4101	221054	59733627577	1292	0.0058447	04101	349126670
4101092003	04101	94	2017	La Serena	270221.9	2017	4101	221054	59733627577	740	0.0033476	04101	199964192
4101092034	04101	46	2017	La Serena	270221.9	2017	4101	221054	59733627577	742	0.0033566	04101	200504635
4101092038	04101	6	2017	La Serena	270221.9	2017	4101	221054	59733627577	329	0.0014883	04101	88902999
4101092039	04101	7	2017	La Serena	270221.9	2017	4101	221054	59733627577	63	0.0002850	04101	17023978
4101092901	04101	2	2017	La Serena	270221.9	2017	4101	221054	59733627577	60	0.0002714	04101	16213313
4101102003	04101	9	2017	La Serena	270221.9	2017	4101	221054	59733627577	70	0.0003167	04101	18915532
4101102013	04101	49	2017	La Serena	270221.9	2017	4101	221054	59733627577	1201	0.0054331	04101	324536479
4101102015	04101	21	2017	La Serena	270221.9	2017	4101	221054	59733627577	364	0.0016467	04101	98360765
4101102020	04101	169	2017	La Serena	270221.9	2017	4101	221054	59733627577	2212	0.0100066	04101	597730800
4101102032	04101	1	2017	La Serena	270221.9	2017	4101	221054	59733627577	48	0.0002171	04101	12970650
4101122010	04101	1	2017	La Serena	270221.9	2017	4101	221054	59733627577	44	0.0001990	04101	11889763
4101132025	04101	30	2017	La Serena	270221.9	2017	4101	221054	59733627577	987	0.0044650	04101	266708996
4101132032	04101	19	2017	La Serena	270221.9	2017	4101	221054	59733627577	824	0.0037276	04101	222662830
4101132046	04101	1	2017	La Serena	270221.9	2017	4101	221054	59733627577	23	0.0001040	04101	6215103
4101132055	04101	1	2017	La Serena	270221.9	2017	4101	221054	59733627577	23	0.0001040	04101	6215103
4101132901	04101	1	2017	La Serena	270221.9	2017	4101	221054	59733627577	36	0.0001629	04101	9727988
4101141001	04101	154	2017	La Serena	270221.9	2017	4101	221054	59733627577	2872	0.0129923	04101	776077241
4101141002	04101	175	2017	La Serena	270221.9	2017	4101	221054	59733627577	2750	0.0124404	04101	743110171
4101141003	04101	378	2017	La Serena	270221.9	2017	4101	221054	59733627577	4706	0.0212889	04101	1271664170
4101141004	04101	229	2017	La Serena	270221.9	2017	4101	221054	59733627577	3750	0.0169642	04101	1013332052
4101141005	04101	510	2017	La Serena	270221.9	2017	4101	221054	59733627577	5866	0.0265365	04101	1585121551
4101141006	04101	194	2017	La Serena	270221.9	2017	4101	221054	59733627577	2114	0.0095633	04101	571249055
4101142008	04101	6	2017	La Serena	270221.9	2017	4101	221054	59733627577	95	0.0004298	04101	25671079
4101142012	04101	25	2017	La Serena	270221.9	2017	4101	221054	59733627577	175	0.0007917	04101	47288829
4101142014	04101	23	2017	La Serena	270221.9	2017	4101	221054	59733627577	519	0.0023478	04101	140245156
4101142019	04101	3	2017	La Serena	270221.9	2017	4101	221054	59733627577	194	0.0008776	04101	52423045
4101142030	04101	2	2017	La Serena	270221.9	2017	4101	221054	59733627577	147	0.0006650	04101	39722616
4101142033	04101	10	2017	La Serena	270221.9	2017	4101	221054	59733627577	51	0.0002307	04101	13781316
4101142036	04101	4	2017	La Serena	270221.9	2017	4101	221054	59733627577	225	0.0010179	04101	60799923
4101142040	04101	1	2017	La Serena	270221.9	2017	4101	221054	59733627577	92	0.0004162	04101	24860413
4101142056	04101	98	2017	La Serena	270221.9	2017	4101	221054	59733627577	383	0.0017326	04101	103494980
4101142057	04101	5	2017	La Serena	270221.9	2017	4101	221054	59733627577	45	0.0002036	04101	12159985
4101142901	04101	36	2017	La Serena	270221.9	2017	4101	221054	59733627577	324	0.0014657	04101	87551889
4101151001	04101	1228	2017	La Serena	270221.9	2017	4101	221054	59733627577	4957	0.0224244	04101	1339489862
4101151002	04101	372	2017	La Serena	270221.9	2017	4101	221054	59733627577	1602	0.0072471	04101	432895453
4101151003	04101	391	2017	La Serena	270221.9	2017	4101	221054	59733627577	1900	0.0085952	04101	513421573
4101151004	04101	372	2017	La Serena	270221.9	2017	4101	221054	59733627577	2649	0.0119835	04101	715817762
4101151005	04101	506	2017	La Serena	270221.9	2017	4101	221054	59733627577	2047	0.0092602	04101	553144189
4101151006	04101	569	2017	La Serena	270221.9	2017	4101	221054	59733627577	3173	0.0143540	04101	857414027
4101161001	04101	241	2017	La Serena	270221.9	2017	4101	221054	59733627577	5756	0.0260389	04101	1555397144
4101161002	04101	183	2017	La Serena	270221.9	2017	4101	221054	59733627577	3690	0.0166928	04101	997118739
4101161003	04101	130	2017	La Serena	270221.9	2017	4101	221054	59733627577	2952	0.0133542	04101	797694991

7 Análisis de regresión

Aplicaremos un análisis de regresión donde:

\[ Y(dependiente) = ingreso \ expandido \ por \ zona \ (multi\_pob)\]

\[ X(independiente) = frecuencia \ de \ población \ que \ posee \ la \ variable \ Censal \ respecto \ a \ la \ zona \ (Freq.x) \]

7.1 Diagrama de dispersión

scatter.smooth(x=h_y_m_comuna_corr_01$Freq.x, y=h_y_m_comuna_corr_01$multi_pob, main="multi_pob ~ Freq.x",
     xlab = "Freq.x",
     ylab = "multi_pob",
           col = 2) 

7.2 Outliers

Hemos demostrado en el punto 5.7.2 de aquí que la exclusión de ouliers no genera ninguna mejora en el modelo de regresión.

7.3 Modelo lineal

Aplicaremos un análisis de regresión lineal del ingreso expandido por zona sobre las frecuencias de respuestas zonales.

linearMod <- lm( multi_pob~(Freq.x) , data=h_y_m_comuna_corr_01)
summary(linearMod) 

## 
## Call:
## lm(formula = multi_pob ~ (Freq.x), data = h_y_m_comuna_corr_01)
## 
## Residuals:
##        Min         1Q     Median         3Q        Max 
## -1.132e+09 -1.421e+08 -1.062e+08  3.801e+07  1.171e+09 
## 
## Coefficients:
##              Estimate Std. Error t value Pr(>|t|)    
## (Intercept) 151825903   12814562   11.85   <2e-16 ***
## Freq.x        1785288      63820   27.97   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 290600000 on 625 degrees of freedom
## Multiple R-squared:  0.556,  Adjusted R-squared:  0.5552 
## F-statistic: 782.5 on 1 and 625 DF,  p-value: < 2.2e-16

7.4 Gráfica de la recta de regresión lineal

ggplot(h_y_m_comuna_corr_01, aes(x = Freq.x , y = multi_pob)) + 
  geom_point() +
  stat_smooth(method = "lm", col = "red")

Si bien obtenemos nuestro modelo lineal da cuenta del 0.8214 de la variabilidad de los datos de respuesta en torno a su media, modelos alternativos pueden ofrecernos una explicación de la variable dependiente aún mayor.

8 Modelos alternativos

8.1 Modelo cuadrático

\[ \hat Y = \beta_0 + \beta_1 X^2 \]

linearMod <- lm( multi_pob~(Freq.x^2) , data=h_y_m_comuna_corr_01)
summary(linearMod) 

## 
## Call:
## lm(formula = multi_pob ~ (Freq.x^2), data = h_y_m_comuna_corr_01)
## 
## Residuals:
##        Min         1Q     Median         3Q        Max 
## -1.132e+09 -1.421e+08 -1.062e+08  3.801e+07  1.171e+09 
## 
## Coefficients:
##              Estimate Std. Error t value Pr(>|t|)    
## (Intercept) 151825903   12814562   11.85   <2e-16 ***
## Freq.x        1785288      63820   27.97   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 290600000 on 625 degrees of freedom
## Multiple R-squared:  0.556,  Adjusted R-squared:  0.5552 
## F-statistic: 782.5 on 1 and 625 DF,  p-value: < 2.2e-16

8.2 Modelo cúbico

\[ \hat Y = \beta_0 + \beta_1 X^3 \]

linearMod <- lm( multi_pob~(Freq.x^3) , data=h_y_m_comuna_corr_01)
summary(linearMod) 

## 
## Call:
## lm(formula = multi_pob ~ (Freq.x^3), data = h_y_m_comuna_corr_01)
## 
## Residuals:
##        Min         1Q     Median         3Q        Max 
## -1.132e+09 -1.421e+08 -1.062e+08  3.801e+07  1.171e+09 
## 
## Coefficients:
##              Estimate Std. Error t value Pr(>|t|)    
## (Intercept) 151825903   12814562   11.85   <2e-16 ***
## Freq.x        1785288      63820   27.97   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 290600000 on 625 degrees of freedom
## Multiple R-squared:  0.556,  Adjusted R-squared:  0.5552 
## F-statistic: 782.5 on 1 and 625 DF,  p-value: < 2.2e-16

8.3 Modelo logarítmico

\[ \hat Y = \beta_0 + \beta_1 ln X \]

linearMod <- lm( multi_pob~log(Freq.x) , data=h_y_m_comuna_corr_01)
summary(linearMod) 

## 
## Call:
## lm(formula = multi_pob ~ log(Freq.x), data = h_y_m_comuna_corr_01)
## 
## Residuals:
##        Min         1Q     Median         3Q        Max 
## -557337281 -163222717  -18733565  169628646 1100583501 
## 
## Coefficients:
##               Estimate Std. Error t value Pr(>|t|)    
## (Intercept) -164709579   15732599  -10.47   <2e-16 ***
## log(Freq.x)  180054023    4780588   37.66   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 241200000 on 625 degrees of freedom
## Multiple R-squared:  0.6942, Adjusted R-squared:  0.6937 
## F-statistic:  1419 on 1 and 625 DF,  p-value: < 2.2e-16

8.4 Modelo exponencial

\[ \hat Y = \beta_0 + \beta_1 e^X \]

No es aplicable sin una transformación pues los valores elevados a \(e\) de Freq.x tienden a infinito.

8.5 Modelo con raíz cuadrada

\[ \hat Y = \beta_0 + \beta_1 \sqrt {X} \]

linearMod <- lm( multi_pob~sqrt(Freq.x) , data=h_y_m_comuna_corr_01)
summary(linearMod) 

## 
## Call:
## lm(formula = multi_pob ~ sqrt(Freq.x), data = h_y_m_comuna_corr_01)
## 
## Residuals:
##        Min         1Q     Median         3Q        Max 
## -773146595  -69941350  -20094906   23992146  940903693 
## 
## Coefficients:
##               Estimate Std. Error t value Pr(>|t|)    
## (Intercept)  -41019228   11367738  -3.608 0.000333 ***
## sqrt(Freq.x)  55697638    1232068  45.207  < 2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 211100000 on 625 degrees of freedom
## Multiple R-squared:  0.7658, Adjusted R-squared:  0.7654 
## F-statistic:  2044 on 1 and 625 DF,  p-value: < 2.2e-16

8.6 Modelo raíz-raíz

\[ \hat Y = {\beta_0}^2 + 2 \beta_0 \beta_1 \sqrt{X}+ \beta_1^2 X \]

linearMod <- lm( sqrt(multi_pob)~sqrt(Freq.x) , data=h_y_m_comuna_corr_01)
summary(linearMod) 

## 
## Call:
## lm(formula = sqrt(multi_pob) ~ sqrt(Freq.x), data = h_y_m_comuna_corr_01)
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
## -20278.7  -3086.8   -737.6   2686.1  16347.3 
## 
## Coefficients:
##              Estimate Std. Error t value Pr(>|t|)    
## (Intercept)   4439.50     285.62   15.54   <2e-16 ***
## sqrt(Freq.x)  1441.29      30.96   46.56   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 5303 on 625 degrees of freedom
## Multiple R-squared:  0.7762, Adjusted R-squared:  0.7758 
## F-statistic:  2168 on 1 and 625 DF,  p-value: < 2.2e-16

8.7 Modelo log-raíz

\[ \hat Y = e^{\beta_0 + \beta_1 \sqrt{X}} \]

linearMod <- lm( log(multi_pob)~sqrt(Freq.x) , data=h_y_m_comuna_corr_01)
summary(linearMod) 

## 
## Call:
## lm(formula = log(multi_pob) ~ sqrt(Freq.x), data = h_y_m_comuna_corr_01)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -3.5818 -0.7651  0.1520  0.8381  2.4974 
## 
## Coefficients:
##               Estimate Std. Error t value Pr(>|t|)    
## (Intercept)  16.999397   0.059155  287.37   <2e-16 ***
## sqrt(Freq.x)  0.204006   0.006411   31.82   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.098 on 625 degrees of freedom
## Multiple R-squared:  0.6183, Adjusted R-squared:  0.6177 
## F-statistic:  1012 on 1 and 625 DF,  p-value: < 2.2e-16

8.8 Modelo raíz-log

\[ \hat Y = {\beta_0}^2 + 2 \beta_0 \beta_1 \ln{X}+ \beta_1^2 ln^2X \]

linearMod <- lm( sqrt(multi_pob)~log(Freq.x) , data=h_y_m_comuna_corr_01)
summary(linearMod) 

## 
## Call:
## lm(formula = sqrt(multi_pob) ~ log(Freq.x), data = h_y_m_comuna_corr_01)
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
## -13114.3  -3243.4    -45.6   3013.9  14351.0 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)   338.14     317.03   1.067    0.287    
## log(Freq.x)  5005.37      96.33  51.958   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 4860 on 625 degrees of freedom
## Multiple R-squared:  0.812,  Adjusted R-squared:  0.8117 
## F-statistic:  2700 on 1 and 625 DF,  p-value: < 2.2e-16

8.9 Modelo log-log

\[ \hat Y = e^{\beta_0+\beta_1 ln{X}} \]

linearMod <- lm( log(multi_pob)~log(Freq.x) , data=h_y_m_comuna_corr_01)
summary(linearMod) 

## 
## Call:
## lm(formula = log(multi_pob) ~ log(Freq.x), data = h_y_m_comuna_corr_01)
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
## -2.59410 -0.52576  0.06455  0.53118  2.26833 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept) 16.21575    0.05222  310.54   <2e-16 ***
## log(Freq.x)  0.78654    0.01587   49.57   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 0.8005 on 625 degrees of freedom
## Multiple R-squared:  0.7972, Adjusted R-squared:  0.7969 
## F-statistic:  2457 on 1 and 625 DF,  p-value: < 2.2e-16

9 Modelo raíz-log (r-log)

Es éste el modelo que nos entrega el mayor coeficiente de determinación de todos (0.8117).

9.1 Diagrama de dispersión sobre r-log

Desplegamos una curva suavizada por loess en el diagrama de dispersión.

scatter.smooth(x=sqrt(h_y_m_comuna_corr_01$Freq.x), y=log(h_y_m_comuna_corr_01$multi_pob), lpars = list(col = "red", lwd = 2, lty = 1), main="multi_pob ~ Freq.x")

9.2 Modelo r-log

Observemos nuevamente el resultado sobre r-log.

linearMod <- lm(sqrt( multi_pob)~log(Freq.x) , data=h_y_m_comuna_corr_01)
summary(linearMod) 

## 
## Call:
## lm(formula = sqrt(multi_pob) ~ log(Freq.x), data = h_y_m_comuna_corr_01)
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
## -13114.3  -3243.4    -45.6   3013.9  14351.0 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)   338.14     317.03   1.067    0.287    
## log(Freq.x)  5005.37      96.33  51.958   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 4860 on 625 degrees of freedom
## Multiple R-squared:  0.812,  Adjusted R-squared:  0.8117 
## F-statistic:  2700 on 1 and 625 DF,  p-value: < 2.2e-16

ggplot(h_y_m_comuna_corr_01, aes(x = sqrt(Freq.x) , y = log(multi_pob))) + 
  geom_point() +
  stat_smooth(method = "lm", col = "red")

9.3 Análisis de residuos

par(mfrow = c (2,2))
plot(linearMod)

9.4 Ecuación del modelo

\[ \hat Y = 338.14^2 + 2 \cdot 338.14 \cdot 5005.37 \cdot ln{X} + 5005.37 ^2 \cdot ln ^2 X \]

10 Aplicación la regresión a los valores de la variable a nivel de zona

Esta nueva variable se llamará: est_ing

h_y_m_comuna_corr_01$est_ing <- 338.14^2 + 2  * 338.14 * 5005.37 * log(h_y_m_comuna_corr_01$Freq.x)+ 5005.37 ^2 * {log(h_y_m_comuna_corr_01$Freq.x)}^2

r3_100 <- h_y_m_comuna_corr_01[c(1:100),]
kbl(r3_100) %>%
  kable_styling(bootstrap_options = c("striped", "hover")) %>%
  kable_paper() %>%
  scroll_box(width = "100%", height = "300px")

zona	código.x	Freq.x	anio	comuna.x	promedio_i	año	comuna.y	personas	Ingresos_expandidos	Freq.y	p_poblacional	código.y	multi_pob	est_ing
4101011001	04101	119	2017	La Serena	270221.9	2017	4101	221054	59733627577	1455	0.0065821	04101	393172836	588519524.7
4101021001	04101	89	2017	La Serena	270221.9	2017	4101	221054	59733627577	2431	0.0109973	04101	656909392	520087447.1
4101021002	04101	108	2017	La Serena	270221.9	2017	4101	221054	59733627577	2926	0.0132366	04101	790669222	565200184.1
4101021003	04101	158	2017	La Serena	270221.9	2017	4101	221054	59733627577	2699	0.0122097	04101	729328856	659375157.7
4101021004	04101	222	2017	La Serena	270221.9	2017	4101	221054	59733627577	5323	0.0240801	04101	1438391070	749693931.6
4101021005	04101	217	2017	La Serena	270221.9	2017	4101	221054	59733627577	2125	0.0096130	04101	574221496	743462939.3
4101022001	04101	85	2017	La Serena	270221.9	2017	4101	221054	59733627577	1157	0.0052340	04101	312646716	509642062.4
4101031001	04101	1023	2017	La Serena	270221.9	2017	4101	221054	59733627577	4341	0.0196377	04101	1173033183	1226948915.6
4101031002	04101	172	2017	La Serena	270221.9	2017	4101	221054	59733627577	2583	0.0116849	04101	697983117	681379891.8
4101031003	04101	670	2017	La Serena	270221.9	2017	4101	221054	59733627577	4026	0.0182127	04101	1087913291	1083033389.7
4101041001	04101	153	2017	La Serena	270221.9	2017	4101	221054	59733627577	1108	0.0050123	04101	299405844	651134796.8
4101041002	04101	89	2017	La Serena	270221.9	2017	4101	221054	59733627577	1015	0.0045916	04101	274275209	520087447.1
4101041003	04101	952	2017	La Serena	270221.9	2017	4101	221054	59733627577	4721	0.0213568	04101	1275717498	1201856056.5
4101041004	04101	452	2017	La Serena	270221.9	2017	4101	221054	59733627577	3560	0.0161047	04101	961989895	957245319.7
4101041005	04101	148	2017	La Serena	270221.9	2017	4101	221054	59733627577	812	0.0036733	04101	219420167	642675046.5
4101041006	04101	130	2017	La Serena	270221.9	2017	4101	221054	59733627577	821	0.0037140	04101	221852164	610186378.9
4101051001	04101	118	2017	La Serena	270221.9	2017	4101	221054	59733627577	1419	0.0064192	04101	383444848	586471889.4
4101051002	04101	216	2017	La Serena	270221.9	2017	4101	221054	59733627577	2920	0.0132094	04101	789047891	742202695.5
4101051003	04101	372	2017	La Serena	270221.9	2017	4101	221054	59733627577	3348	0.0151456	04101	904702856	897864891.7
4101051004	04101	286	2017	La Serena	270221.9	2017	4101	221054	59733627577	2851	0.0128973	04101	770402581	820734932.5
4101051005	04101	661	2017	La Serena	270221.9	2017	4101	221054	59733627577	5493	0.0248491	04101	1484328790	1078582556.7
4101051006	04101	1199	2017	La Serena	270221.9	2017	4101	221054	59733627577	4295	0.0194296	04101	1160602977	1283246133.7
4101051007	04101	560	2017	La Serena	270221.9	2017	4101	221054	59733627577	2336	0.0105676	04101	631238313	1024755655.5
4101051008	04101	1047	2017	La Serena	270221.9	2017	4101	221054	59733627577	4235	0.0191582	04101	1144389664	1235093871.6
4101051009	04101	1119	2017	La Serena	270221.9	2017	4101	221054	59733627577	3882	0.0175613	04101	1049001340	1258602768.2
4101051010	04101	630	2017	La Serena	270221.9	2017	4101	221054	59733627577	3226	0.0145937	04101	871735787	1062848192.2
4101051011	04101	712	2017	La Serena	270221.9	2017	4101	221054	59733627577	2966	0.0134175	04101	801478098	1103156519.4
4101052007	04101	20	2017	La Serena	270221.9	2017	4101	221054	59733627577	125	0.0005655	04101	33777735	235097468.2
4101061001	04101	253	2017	La Serena	270221.9	2017	4101	221054	59733627577	4424	0.0200132	04101	1195461599	785950108.9
4101061002	04101	349	2017	La Serena	270221.9	2017	4101	221054	59733627577	3047	0.0137840	04101	823366070	878822547.5
4101061003	04101	679	2017	La Serena	270221.9	2017	4101	221054	59733627577	3472	0.0157066	04101	938210369	1087433814.2
4101061004	04101	755	2017	La Serena	270221.9	2017	4101	221054	59733627577	5333	0.0241253	04101	1441093289	1122740106.3
4101061005	04101	35	2017	La Serena	270221.9	2017	4101	221054	59733627577	288	0.0013028	04101	77823902	328840959.6
4101062001	04101	48	2017	La Serena	270221.9	2017	4101	221054	59733627577	345	0.0015607	04101	93226549	388678599.1
4101062004	04101	114	2017	La Serena	270221.9	2017	4101	221054	59733627577	740	0.0033476	04101	199964192	578141136.2
4101062006	04101	25	2017	La Serena	270221.9	2017	4101	221054	59733627577	224	0.0010133	04101	60529701	270596067.7
4101062024	04101	15	2017	La Serena	270221.9	2017	4101	221054	59733627577	2392	0.0108209	04101	646370738	193013593.9
4101062030	04101	1	2017	La Serena	270221.9	2017	4101	221054	59733627577	41	0.0001855	04101	11079097	114338.7
4101062049	04101	25	2017	La Serena	270221.9	2017	4101	221054	59733627577	115	0.0005202	04101	31075516	270596067.7
4101062901	04101	11	2017	La Serena	270221.9	2017	4101	221054	59733627577	284	0.0012848	04101	76743014	152287769.0
4101071001	04101	35	2017	La Serena	270221.9	2017	4101	221054	59733627577	1056	0.0047771	04101	285354306	328840959.6
4101072002	04101	55	2017	La Serena	270221.9	2017	4101	221054	59733627577	394	0.0017824	04101	106467421	416010086.0
4101072027	04101	17	2017	La Serena	270221.9	2017	4101	221054	59733627577	461	0.0020855	04101	124572287	210813588.4
4101072029	04101	3	2017	La Serena	270221.9	2017	4101	221054	59733627577	119	0.0005383	04101	32156404	34071748.0
4101072051	04101	20	2017	La Serena	270221.9	2017	4101	221054	59733627577	179	0.0008098	04101	48369717	235097468.2
4101072053	04101	2	2017	La Serena	270221.9	2017	4101	221054	59733627577	35	0.0001583	04101	9457766	14497803.3
4101072054	04101	4	2017	La Serena	270221.9	2017	4101	221054	59733627577	114	0.0005157	04101	30805294	52955547.0
4101082011	04101	8	2017	La Serena	270221.9	2017	4101	221054	59733627577	304	0.0013752	04101	82147452	115487569.8
4101082018	04101	25	2017	La Serena	270221.9	2017	4101	221054	59733627577	348	0.0015743	04101	94037214	270596067.7
4101082021	04101	61	2017	La Serena	270221.9	2017	4101	221054	59733627577	748	0.0033838	04101	202125967	437419853.7
4101082022	04101	1	2017	La Serena	270221.9	2017	4101	221054	59733627577	13	0.0000588	04101	3512884	114338.7
4101082023	04101	46	2017	La Serena	270221.9	2017	4101	221054	59733627577	733	0.0033159	04101	198072638	380324368.3
4101082029	04101	7	2017	La Serena	270221.9	2017	4101	221054	59733627577	140	0.0006333	04101	37831063	101568911.6
4101082043	04101	38	2017	La Serena	270221.9	2017	4101	221054	59733627577	692	0.0031305	04101	186993541	343939451.3
4101082051	04101	5	2017	La Serena	270221.9	2017	4101	221054	59733627577	36	0.0001629	04101	9727988	70458770.0
4101082052	04101	5	2017	La Serena	270221.9	2017	4101	221054	59733627577	52	0.0002352	04101	14051538	70458770.0
4101082901	04101	6	2017	La Serena	270221.9	2017	4101	221054	59733627577	37	0.0001674	04101	9998210	86612042.2
4101091001	04101	41	2017	La Serena	270221.9	2017	4101	221054	59733627577	1292	0.0058447	04101	349126670	358191288.7
4101092003	04101	94	2017	La Serena	270221.9	2017	4101	221054	59733627577	740	0.0033476	04101	199964192	532640767.4
4101092034	04101	46	2017	La Serena	270221.9	2017	4101	221054	59733627577	742	0.0033566	04101	200504635	380324368.3
4101092038	04101	6	2017	La Serena	270221.9	2017	4101	221054	59733627577	329	0.0014883	04101	88902999	86612042.2
4101092039	04101	7	2017	La Serena	270221.9	2017	4101	221054	59733627577	63	0.0002850	04101	17023978	101568911.6
4101092901	04101	2	2017	La Serena	270221.9	2017	4101	221054	59733627577	60	0.0002714	04101	16213313	14497803.3
4101102003	04101	9	2017	La Serena	270221.9	2017	4101	221054	59733627577	70	0.0003167	04101	18915532	128506301.3
4101102013	04101	49	2017	La Serena	270221.9	2017	4101	221054	59733627577	1201	0.0054331	04101	324536479	392758695.5
4101102015	04101	21	2017	La Serena	270221.9	2017	4101	221054	59733627577	364	0.0016467	04101	98360765	242646084.1
4101102020	04101	169	2017	La Serena	270221.9	2017	4101	221054	59733627577	2212	0.0100066	04101	597730800	676789649.3
4101102032	04101	1	2017	La Serena	270221.9	2017	4101	221054	59733627577	48	0.0002171	04101	12970650	114338.7
4101122010	04101	1	2017	La Serena	270221.9	2017	4101	221054	59733627577	44	0.0001990	04101	11889763	114338.7
4101132025	04101	30	2017	La Serena	270221.9	2017	4101	221054	59733627577	987	0.0044650	04101	266708996	301452633.0
4101132032	04101	19	2017	La Serena	270221.9	2017	4101	221054	59733627577	824	0.0037276	04101	222662830	227290194.3
4101132046	04101	1	2017	La Serena	270221.9	2017	4101	221054	59733627577	23	0.0001040	04101	6215103	114338.7
4101132055	04101	1	2017	La Serena	270221.9	2017	4101	221054	59733627577	23	0.0001040	04101	6215103	114338.7
4101132901	04101	1	2017	La Serena	270221.9	2017	4101	221054	59733627577	36	0.0001629	04101	9727988	114338.7
4101141001	04101	154	2017	La Serena	270221.9	2017	4101	221054	59733627577	2872	0.0129923	04101	776077241	652800019.0
4101141002	04101	175	2017	La Serena	270221.9	2017	4101	221054	59733627577	2750	0.0124404	04101	743110171	685905873.9
4101141003	04101	378	2017	La Serena	270221.9	2017	4101	221054	59733627577	4706	0.0212889	04101	1271664170	902670860.2
4101141004	04101	229	2017	La Serena	270221.9	2017	4101	221054	59733627577	3750	0.0169642	04101	1013332052	758227391.7
4101141005	04101	510	2017	La Serena	270221.9	2017	4101	221054	59733627577	5866	0.0265365	04101	1585121551	995003269.4
4101141006	04101	194	2017	La Serena	270221.9	2017	4101	221054	59733627577	2114	0.0095633	04101	571249055	713195437.6
4101142008	04101	6	2017	La Serena	270221.9	2017	4101	221054	59733627577	95	0.0004298	04101	25671079	86612042.2
4101142012	04101	25	2017	La Serena	270221.9	2017	4101	221054	59733627577	175	0.0007917	04101	47288829	270596067.7
4101142014	04101	23	2017	La Serena	270221.9	2017	4101	221054	59733627577	519	0.0023478	04101	140245156	257039410.8
4101142019	04101	3	2017	La Serena	270221.9	2017	4101	221054	59733627577	194	0.0008776	04101	52423045	34071748.0
4101142030	04101	2	2017	La Serena	270221.9	2017	4101	221054	59733627577	147	0.0006650	04101	39722616	14497803.3
4101142033	04101	10	2017	La Serena	270221.9	2017	4101	221054	59733627577	51	0.0002307	04101	13781316	140740979.6
4101142036	04101	4	2017	La Serena	270221.9	2017	4101	221054	59733627577	225	0.0010179	04101	60799923	52955547.0
4101142040	04101	1	2017	La Serena	270221.9	2017	4101	221054	59733627577	92	0.0004162	04101	24860413	114338.7
4101142056	04101	98	2017	La Serena	270221.9	2017	4101	221054	59733627577	383	0.0017326	04101	103494980	542312251.8
4101142057	04101	5	2017	La Serena	270221.9	2017	4101	221054	59733627577	45	0.0002036	04101	12159985	70458770.0
4101142901	04101	36	2017	La Serena	270221.9	2017	4101	221054	59733627577	324	0.0014657	04101	87551889	333974827.8
4101151001	04101	1228	2017	La Serena	270221.9	2017	4101	221054	59733627577	4957	0.0224244	04101	1339489862	1291830822.8
4101151002	04101	372	2017	La Serena	270221.9	2017	4101	221054	59733627577	1602	0.0072471	04101	432895453	897864891.7
4101151003	04101	391	2017	La Serena	270221.9	2017	4101	221054	59733627577	1900	0.0085952	04101	513421573	912869466.0
4101151004	04101	372	2017	La Serena	270221.9	2017	4101	221054	59733627577	2649	0.0119835	04101	715817762	897864891.7
4101151005	04101	506	2017	La Serena	270221.9	2017	4101	221054	59733627577	2047	0.0092602	04101	553144189	992518388.6
4101151006	04101	569	2017	La Serena	270221.9	2017	4101	221054	59733627577	3173	0.0143540	04101	857414027	1029871355.9
4101161001	04101	241	2017	La Serena	270221.9	2017	4101	221054	59733627577	5756	0.0260389	04101	1555397144	772371809.2
4101161002	04101	183	2017	La Serena	270221.9	2017	4101	221054	59733627577	3690	0.0166928	04101	997118739	697675396.7
4101161003	04101	130	2017	La Serena	270221.9	2017	4101	221054	59733627577	2952	0.0133542	04101	797694991	610186378.9

11 División del valor estimado entre la población total de la zona para obtener el ingreso medio por zona

\[ Ingreso \_ Medio\_zona = est\_ing / (personas * p\_poblacional) \]

h_y_m_comuna_corr_01$ing_medio_zona <- h_y_m_comuna_corr_01$est_ing  /( h_y_m_comuna_corr_01$personas  * h_y_m_comuna_corr_01$p_poblacional)

r3_100 <- h_y_m_comuna_corr_01[c(1:100),]
kbl(r3_100) %>%
  kable_styling(bootstrap_options = c("striped", "hover")) %>%
  kable_paper() %>%
  scroll_box(width = "100%", height = "300px")

zona	código.x	Freq.x	anio	comuna.x	promedio_i	año	comuna.y	personas	Ingresos_expandidos	Freq.y	p_poblacional	código.y	multi_pob	est_ing	ing_medio_zona
4101011001	04101	119	2017	La Serena	270221.9	2017	4101	221054	59733627577	1455	0.0065821	04101	393172836	588519524.7	404480.773
4101021001	04101	89	2017	La Serena	270221.9	2017	4101	221054	59733627577	2431	0.0109973	04101	656909392	520087447.1	213939.715
4101021002	04101	108	2017	La Serena	270221.9	2017	4101	221054	59733627577	2926	0.0132366	04101	790669222	565200184.1	193164.793
4101021003	04101	158	2017	La Serena	270221.9	2017	4101	221054	59733627577	2699	0.0122097	04101	729328856	659375157.7	244303.504
4101021004	04101	222	2017	La Serena	270221.9	2017	4101	221054	59733627577	5323	0.0240801	04101	1438391070	749693931.6	140840.491
4101021005	04101	217	2017	La Serena	270221.9	2017	4101	221054	59733627577	2125	0.0096130	04101	574221496	743462939.3	349864.913
4101022001	04101	85	2017	La Serena	270221.9	2017	4101	221054	59733627577	1157	0.0052340	04101	312646716	509642062.4	440485.793
4101031001	04101	1023	2017	La Serena	270221.9	2017	4101	221054	59733627577	4341	0.0196377	04101	1173033183	1226948915.6	282641.999
4101031002	04101	172	2017	La Serena	270221.9	2017	4101	221054	59733627577	2583	0.0116849	04101	697983117	681379891.8	263793.996
4101031003	04101	670	2017	La Serena	270221.9	2017	4101	221054	59733627577	4026	0.0182127	04101	1087913291	1083033389.7	269009.784
4101041001	04101	153	2017	La Serena	270221.9	2017	4101	221054	59733627577	1108	0.0050123	04101	299405844	651134796.8	587666.784
4101041002	04101	89	2017	La Serena	270221.9	2017	4101	221054	59733627577	1015	0.0045916	04101	274275209	520087447.1	512401.426
4101041003	04101	952	2017	La Serena	270221.9	2017	4101	221054	59733627577	4721	0.0213568	04101	1275717498	1201856056.5	254576.585
4101041004	04101	452	2017	La Serena	270221.9	2017	4101	221054	59733627577	3560	0.0161047	04101	961989895	957245319.7	268889.135
4101041005	04101	148	2017	La Serena	270221.9	2017	4101	221054	59733627577	812	0.0036733	04101	219420167	642675046.5	791471.732
4101041006	04101	130	2017	La Serena	270221.9	2017	4101	221054	59733627577	821	0.0037140	04101	221852164	610186378.9	743223.360
4101051001	04101	118	2017	La Serena	270221.9	2017	4101	221054	59733627577	1419	0.0064192	04101	383444848	586471889.4	413299.429
4101051002	04101	216	2017	La Serena	270221.9	2017	4101	221054	59733627577	2920	0.0132094	04101	789047891	742202695.5	254179.005
4101051003	04101	372	2017	La Serena	270221.9	2017	4101	221054	59733627577	3348	0.0151456	04101	904702856	897864891.7	268179.478
4101051004	04101	286	2017	La Serena	270221.9	2017	4101	221054	59733627577	2851	0.0128973	04101	770402581	820734932.5	287876.160
4101051005	04101	661	2017	La Serena	270221.9	2017	4101	221054	59733627577	5493	0.0248491	04101	1484328790	1078582556.7	196355.827
4101051006	04101	1199	2017	La Serena	270221.9	2017	4101	221054	59733627577	4295	0.0194296	04101	1160602977	1283246133.7	298776.748
4101051007	04101	560	2017	La Serena	270221.9	2017	4101	221054	59733627577	2336	0.0105676	04101	631238313	1024755655.5	438679.647
4101051008	04101	1047	2017	La Serena	270221.9	2017	4101	221054	59733627577	4235	0.0191582	04101	1144389664	1235093871.6	291639.639
4101051009	04101	1119	2017	La Serena	270221.9	2017	4101	221054	59733627577	3882	0.0175613	04101	1049001340	1258602768.2	324215.036
4101051010	04101	630	2017	La Serena	270221.9	2017	4101	221054	59733627577	3226	0.0145937	04101	871735787	1062848192.2	329463.172
4101051011	04101	712	2017	La Serena	270221.9	2017	4101	221054	59733627577	2966	0.0134175	04101	801478098	1103156519.4	371934.093
4101052007	04101	20	2017	La Serena	270221.9	2017	4101	221054	59733627577	125	0.0005655	04101	33777735	235097468.2	1880779.746
4101061001	04101	253	2017	La Serena	270221.9	2017	4101	221054	59733627577	4424	0.0200132	04101	1195461599	785950108.9	177655.992
4101061002	04101	349	2017	La Serena	270221.9	2017	4101	221054	59733627577	3047	0.0137840	04101	823366070	878822547.5	288422.234
4101061003	04101	679	2017	La Serena	270221.9	2017	4101	221054	59733627577	3472	0.0157066	04101	938210369	1087433814.2	313200.983
4101061004	04101	755	2017	La Serena	270221.9	2017	4101	221054	59733627577	5333	0.0241253	04101	1441093289	1122740106.3	210526.928
4101061005	04101	35	2017	La Serena	270221.9	2017	4101	221054	59733627577	288	0.0013028	04101	77823902	328840959.6	1141808.887
4101062001	04101	48	2017	La Serena	270221.9	2017	4101	221054	59733627577	345	0.0015607	04101	93226549	388678599.1	1126604.635
4101062004	04101	114	2017	La Serena	270221.9	2017	4101	221054	59733627577	740	0.0033476	04101	199964192	578141136.2	781271.806
4101062006	04101	25	2017	La Serena	270221.9	2017	4101	221054	59733627577	224	0.0010133	04101	60529701	270596067.7	1208018.159
4101062024	04101	15	2017	La Serena	270221.9	2017	4101	221054	59733627577	2392	0.0108209	04101	646370738	193013593.9	80691.302
4101062030	04101	1	2017	La Serena	270221.9	2017	4101	221054	59733627577	41	0.0001855	04101	11079097	114338.7	2788.748
4101062049	04101	25	2017	La Serena	270221.9	2017	4101	221054	59733627577	115	0.0005202	04101	31075516	270596067.7	2353009.284
4101062901	04101	11	2017	La Serena	270221.9	2017	4101	221054	59733627577	284	0.0012848	04101	76743014	152287769.0	536224.539
4101071001	04101	35	2017	La Serena	270221.9	2017	4101	221054	59733627577	1056	0.0047771	04101	285354306	328840959.6	311402.424
4101072002	04101	55	2017	La Serena	270221.9	2017	4101	221054	59733627577	394	0.0017824	04101	106467421	416010086.0	1055863.162
4101072027	04101	17	2017	La Serena	270221.9	2017	4101	221054	59733627577	461	0.0020855	04101	124572287	210813588.4	457296.287
4101072029	04101	3	2017	La Serena	270221.9	2017	4101	221054	59733627577	119	0.0005383	04101	32156404	34071748.0	286317.210
4101072051	04101	20	2017	La Serena	270221.9	2017	4101	221054	59733627577	179	0.0008098	04101	48369717	235097468.2	1313393.677
4101072053	04101	2	2017	La Serena	270221.9	2017	4101	221054	59733627577	35	0.0001583	04101	9457766	14497803.3	414222.952
4101072054	04101	4	2017	La Serena	270221.9	2017	4101	221054	59733627577	114	0.0005157	04101	30805294	52955547.0	464522.342
4101082011	04101	8	2017	La Serena	270221.9	2017	4101	221054	59733627577	304	0.0013752	04101	82147452	115487569.8	379893.322
4101082018	04101	25	2017	La Serena	270221.9	2017	4101	221054	59733627577	348	0.0015743	04101	94037214	270596067.7	777574.907
4101082021	04101	61	2017	La Serena	270221.9	2017	4101	221054	59733627577	748	0.0033838	04101	202125967	437419853.7	584785.901
4101082022	04101	1	2017	La Serena	270221.9	2017	4101	221054	59733627577	13	0.0000588	04101	3512884	114338.7	8795.282
4101082023	04101	46	2017	La Serena	270221.9	2017	4101	221054	59733627577	733	0.0033159	04101	198072638	380324368.3	518859.984
4101082029	04101	7	2017	La Serena	270221.9	2017	4101	221054	59733627577	140	0.0006333	04101	37831063	101568911.6	725492.225
4101082043	04101	38	2017	La Serena	270221.9	2017	4101	221054	59733627577	692	0.0031305	04101	186993541	343939451.3	497022.329
4101082051	04101	5	2017	La Serena	270221.9	2017	4101	221054	59733627577	36	0.0001629	04101	9727988	70458770.0	1957188.056
4101082052	04101	5	2017	La Serena	270221.9	2017	4101	221054	59733627577	52	0.0002352	04101	14051538	70458770.0	1354976.347
4101082901	04101	6	2017	La Serena	270221.9	2017	4101	221054	59733627577	37	0.0001674	04101	9998210	86612042.2	2340866.005
4101091001	04101	41	2017	La Serena	270221.9	2017	4101	221054	59733627577	1292	0.0058447	04101	349126670	358191288.7	277237.840
4101092003	04101	94	2017	La Serena	270221.9	2017	4101	221054	59733627577	740	0.0033476	04101	199964192	532640767.4	719784.821
4101092034	04101	46	2017	La Serena	270221.9	2017	4101	221054	59733627577	742	0.0033566	04101	200504635	380324368.3	512566.534
4101092038	04101	6	2017	La Serena	270221.9	2017	4101	221054	59733627577	329	0.0014883	04101	88902999	86612042.2	263258.487
4101092039	04101	7	2017	La Serena	270221.9	2017	4101	221054	59733627577	63	0.0002850	04101	17023978	101568911.6	1612204.945
4101092901	04101	2	2017	La Serena	270221.9	2017	4101	221054	59733627577	60	0.0002714	04101	16213313	14497803.3	241630.055
4101102003	04101	9	2017	La Serena	270221.9	2017	4101	221054	59733627577	70	0.0003167	04101	18915532	128506301.3	1835804.304
4101102013	04101	49	2017	La Serena	270221.9	2017	4101	221054	59733627577	1201	0.0054331	04101	324536479	392758695.5	327026.391
4101102015	04101	21	2017	La Serena	270221.9	2017	4101	221054	59733627577	364	0.0016467	04101	98360765	242646084.1	666610.121
4101102020	04101	169	2017	La Serena	270221.9	2017	4101	221054	59733627577	2212	0.0100066	04101	597730800	676789649.3	305962.771
4101102032	04101	1	2017	La Serena	270221.9	2017	4101	221054	59733627577	48	0.0002171	04101	12970650	114338.7	2382.055
4101122010	04101	1	2017	La Serena	270221.9	2017	4101	221054	59733627577	44	0.0001990	04101	11889763	114338.7	2598.606
4101132025	04101	30	2017	La Serena	270221.9	2017	4101	221054	59733627577	987	0.0044650	04101	266708996	301452633.0	305423.134
4101132032	04101	19	2017	La Serena	270221.9	2017	4101	221054	59733627577	824	0.0037276	04101	222662830	227290194.3	275837.614
4101132046	04101	1	2017	La Serena	270221.9	2017	4101	221054	59733627577	23	0.0001040	04101	6215103	114338.7	4971.246
4101132055	04101	1	2017	La Serena	270221.9	2017	4101	221054	59733627577	23	0.0001040	04101	6215103	114338.7	4971.246
4101132901	04101	1	2017	La Serena	270221.9	2017	4101	221054	59733627577	36	0.0001629	04101	9727988	114338.7	3176.074
4101141001	04101	154	2017	La Serena	270221.9	2017	4101	221054	59733627577	2872	0.0129923	04101	776077241	652800019.0	227298.057
4101141002	04101	175	2017	La Serena	270221.9	2017	4101	221054	59733627577	2750	0.0124404	04101	743110171	685905873.9	249420.318
4101141003	04101	378	2017	La Serena	270221.9	2017	4101	221054	59733627577	4706	0.0212889	04101	1271664170	902670860.2	191812.762
4101141004	04101	229	2017	La Serena	270221.9	2017	4101	221054	59733627577	3750	0.0169642	04101	1013332052	758227391.7	202193.971
4101141005	04101	510	2017	La Serena	270221.9	2017	4101	221054	59733627577	5866	0.0265365	04101	1585121551	995003269.4	169622.105
4101141006	04101	194	2017	La Serena	270221.9	2017	4101	221054	59733627577	2114	0.0095633	04101	571249055	713195437.6	337367.757
4101142008	04101	6	2017	La Serena	270221.9	2017	4101	221054	59733627577	95	0.0004298	04101	25671079	86612042.2	911705.707
4101142012	04101	25	2017	La Serena	270221.9	2017	4101	221054	59733627577	175	0.0007917	04101	47288829	270596067.7	1546263.244
4101142014	04101	23	2017	La Serena	270221.9	2017	4101	221054	59733627577	519	0.0023478	04101	140245156	257039410.8	495258.980
4101142019	04101	3	2017	La Serena	270221.9	2017	4101	221054	59733627577	194	0.0008776	04101	52423045	34071748.0	175627.567
4101142030	04101	2	2017	La Serena	270221.9	2017	4101	221054	59733627577	147	0.0006650	04101	39722616	14497803.3	98624.512
4101142033	04101	10	2017	La Serena	270221.9	2017	4101	221054	59733627577	51	0.0002307	04101	13781316	140740979.6	2759627.051
4101142036	04101	4	2017	La Serena	270221.9	2017	4101	221054	59733627577	225	0.0010179	04101	60799923	52955547.0	235357.987
4101142040	04101	1	2017	La Serena	270221.9	2017	4101	221054	59733627577	92	0.0004162	04101	24860413	114338.7	1242.812
4101142056	04101	98	2017	La Serena	270221.9	2017	4101	221054	59733627577	383	0.0017326	04101	103494980	542312251.8	1415958.882
4101142057	04101	5	2017	La Serena	270221.9	2017	4101	221054	59733627577	45	0.0002036	04101	12159985	70458770.0	1565750.445
4101142901	04101	36	2017	La Serena	270221.9	2017	4101	221054	59733627577	324	0.0014657	04101	87551889	333974827.8	1030786.506
4101151001	04101	1228	2017	La Serena	270221.9	2017	4101	221054	59733627577	4957	0.0224244	04101	1339489862	1291830822.8	260607.388
4101151002	04101	372	2017	La Serena	270221.9	2017	4101	221054	59733627577	1602	0.0072471	04101	432895453	897864891.7	560464.976
4101151003	04101	391	2017	La Serena	270221.9	2017	4101	221054	59733627577	1900	0.0085952	04101	513421573	912869466.0	480457.614
4101151004	04101	372	2017	La Serena	270221.9	2017	4101	221054	59733627577	2649	0.0119835	04101	715817762	897864891.7	338944.844
4101151005	04101	506	2017	La Serena	270221.9	2017	4101	221054	59733627577	2047	0.0092602	04101	553144189	992518388.6	484864.870
4101151006	04101	569	2017	La Serena	270221.9	2017	4101	221054	59733627577	3173	0.0143540	04101	857414027	1029871355.9	324573.387
4101161001	04101	241	2017	La Serena	270221.9	2017	4101	221054	59733627577	5756	0.0260389	04101	1555397144	772371809.2	134185.512
4101161002	04101	183	2017	La Serena	270221.9	2017	4101	221054	59733627577	3690	0.0166928	04101	997118739	697675396.7	189071.923
4101161003	04101	130	2017	La Serena	270221.9	2017	4101	221054	59733627577	2952	0.0133542	04101	797694991	610186378.9	206702.703

Guardamos:

saveRDS(h_y_m_comuna_corr_01, "casen_censo_region_04.rds")

12 Referencias

https://rpubs.com/osoramirez/316691

https://dataintelligencechile.shinyapps.io/casenfinal

Manual_de_usuario_Censo_2017_16R.pdf

http://www.censo2017.cl/microdatos/

Censo de Población y Vivienda

https://www.ine.cl/estadisticas/sociales/censos-de-poblacion-y-vivienda/poblacion-y-vivienda

http://r-statistics.co/Linear-Regression.html