LATITUD

UNIVERSIDAD CENTRAL DEL ECUADOR

ESTUDIO ESTADÍSTICO DE LA CONTAMINACIÓN DEL SUELO Y SU IMPACTO EN LA SALUD

FECHA: 19/11/2025

library(dplyr)

# Cargar datos
datos <- read.csv("soil_pollution_diseases.csv")
centroides <- read.csv("centroides_10_paises.csv")

# Cambiar United States por USA
centroides$Pais[centroides$Pais == "United States"] <- "USA"

# Renombrar columna
colnames(centroides)[colnames(centroides) == "Pais"] <- "Country"

# Unir datasets
datos_final <- datos %>%
  left_join(centroides, by = "Country")


Latitud <- datos_final$Latitud
Latitud <- as.numeric(Latitud)

minL <- min(Latitud)
maxL <- max(Latitud)
min <-min(Latitud)
max <-max(Latitud)
R <-max-min
K <- floor(1 + 3.33 * log10(length(Latitud)))
A <-R/K

# límites SIN redondeo
breaks <- seq(minL, maxL, length.out = K + 1)

clases <- cut(
  Latitud,
  breaks = breaks,
  include.lowest = TRUE,
  right = TRUE
)

ni <- as.numeric(table(clases))

#Tabla de distribución de frecuencia

#Manualmente
Li <-round(seq(from=min,to=max-A,by=A),2)
Ls <-round(seq(from=min+A,to=max,by=A),2)
Mc <-(Li+Ls)/2
ni<-c()
for (i in 1:K) {
  if (i < K) {
    ni[i] <- length(subset(Latitud, Latitud >= Li[i] & Latitud < Ls[i]))
  } else {
    ni[i] <- length(subset(Latitud, Latitud >= Li[i] & Latitud <= Ls[i]))
  }
}

hi <-ni/sum(ni)*100
Ni_asc<-cumsum(ni)
Hi_asc<-cumsum(hi)
Ni_desc<-rev(cumsum(rev(ni)))
Hi_desc<-rev(cumsum(rev(hi)))

TDF_Latitud <- data.frame(
  Li, Ls, Mc, ni, round(hi, 2), Ni_asc, Ni_desc, round(Hi_asc, 2), round(Hi_desc, 2)
)

colnames(TDF_Latitud) <- c("Li","Ls","Mc","ni","hi","Ni_asc(%)","Ni_desc(%)","Hi_asc","Hi_desc")

#Crear fila de totales

totales<-c(
  Li="-",
  Ls="-",
  Mc="-",
  ni=sum(ni),
  hi=sum(hi),
  Ni_asc="-",
  Ni_desc="-",
  Hi_asc="-",
  Hi_desc="-")

TDF_Latitud<-rbind(TDF_Latitud,totales)

# TABLA 
library(dplyr)
library(gt)

TDF_Latitud %>%
  gt() %>%
  tab_header(
    title = md("*Tabla Nro. 13*"),
    subtitle = md("**Tabla de la Latitud (° ′ ″)**")
  ) %>%
  tab_source_note(
    source_note = md("Autor: Grupo 3")
  ) %>%
  tab_options(
    table.border.top.color = "black",
    table.border.bottom.color = "black",
    table.border.top.style = "solid",
    table.border.bottom.style = "solid",
    column_labels.border.top.color = "black",
    column_labels.border.bottom.color = "black",
    column_labels.border.bottom.width = px(2),
    row.striping.include_table_body = TRUE,
    heading.border.bottom.color = "black",
    heading.border.bottom.width = px(2),
    table_body.hlines.color = "gray",
    table_body.border.bottom.color = "black"
  )

Tabla Nro. 13
Tabla de la Latitud (° ′ ″)
Li	Ls	Mc	ni	hi	Ni_asc(%)	Ni_desc(%)	Hi_asc	Hi_desc
-25.27	-18.9	-22.085	0	0	0	2722	0	100
-18.9	-12.53	-15.715	293	10.76	293	2722	10.76	100
-12.53	-6.16	-9.345	0	0	293	2429	10.76	89.24
-6.16	0.21	-2.975	271	9.96	564	2429	20.72	89.24
0.21	6.58	3.395	0	0	564	2158	20.72	79.28
6.58	12.95	9.765	309	11.35	873	2158	32.07	79.28
12.95	19.32	16.135	0	0	873	1849	32.07	67.93
19.32	25.69	22.505	625	22.96	1498	1849	55.03	67.93
25.69	32.06	28.875	305	11.2	1803	1224	66.24	44.97
32.06	38.43	35.245	636	23.37	2439	919	89.6	33.76
38.43	44.8	41.615	0	0	2439	283	89.6	10.4
44.8	51.17	47.985	283	10.4	2722	283	100	10.4
-	-	-	2722	100	-	-	-	-
Autor: Grupo 3

hist(Latitud)

#Simplificación con el histograma

Hist_Latitud<-hist(Latitud,breaks = 8,plot = F)
k<-length(Hist_Latitud$breaks)
Li<-Hist_Latitud$breaks[1:(length(Hist_Latitud$breaks)-1)]
Ls<-Hist_Latitud$breaks[2:length(Hist_Latitud$breaks)]
ni<-Hist_Latitud$counts
sum(ni)

## [1] 3000

Mc<-Hist_Latitud$mids
hi<-(ni/sum(ni))
sum(hi)

## [1] 1

Ni_asc<-cumsum(ni)
Hi_asc<-cumsum(hi)
Ni_desc<-rev(cumsum(rev(ni)))
Hi_desc<-rev(cumsum(rev(hi)))
TDF_Latitud<-data.frame(Li=round(Li,2),
                        Ls=round(Ls,2),
                        Mc=round(Mc,2),
                        ni=ni,
                        hi=round(hi*100,2),
                        Ni_asc=Ni_asc,
                        Ni_desc=Ni_desc,
                        Hi_asc=round(Hi_asc*100,2),
                        Hi_desc=round(Hi_desc*100,2))
colnames(TDF_Latitud)<-c("Lim inf","Lim sup","MC","ni","hi(%)","Ni asc","Ni desc","Hi asc(%)","Hi desc(%)")

#Crear fila de totales
totales<-c(Li="TOTAL",
           Ls="-",
           Mc="-",
           ni = sum(as.numeric(TDF_Latitud$ni)),
           hi = sum(as.numeric(TDF_Latitud$`hi(%)`)),
           Ni_asc="-",
           Ni_desc="-",
           Hi_asc="-",
           Hi_desc="-")

TDF_Latitud<-rbind(TDF_Latitud,totales)

# TABLA 
library(dplyr)
library(gt)

TDF_Latitud %>%
  gt() %>%
  tab_header(
    title = md("*Tabla Nro. 14*"),
    subtitle = md("**Tabla simplificada de la Latitud (° ′ ″)**")
  ) %>%
  tab_source_note(
    source_note = md("Autor: Grupo 3")
  ) %>%
  tab_options(
    table.border.top.color = "black",
    table.border.bottom.color = "black",
    table.border.top.style = "solid",
    table.border.bottom.style = "solid",
    column_labels.border.top.color = "black",
    column_labels.border.bottom.color = "black",
    column_labels.border.bottom.width = px(2),
    row.striping.include_table_body = TRUE,
    heading.border.bottom.color = "black",
    heading.border.bottom.width = px(2),
    table_body.hlines.color = "gray",
    table_body.border.bottom.color = "black"
  )

Tabla Nro. 14
Tabla simplificada de la Latitud (° ′ ″)
Lim inf	Lim sup	MC	ni	hi(%)	Ni asc	Ni desc	Hi asc(%)	Hi desc(%)
-30	-20	-25	278	9.27	278	3000	9.27	100
-20	-10	-15	293	9.77	571	2722	19.03	90.73
-10	0	-5	271	9.03	842	2429	28.07	80.97
0	10	5	309	10.3	1151	2158	38.37	71.93
10	20	15	0	0	1151	1849	38.37	61.63
20	30	25	625	20.83	1776	1849	59.2	61.63
30	40	35	941	31.37	2717	1224	90.57	40.8
40	50	45	0	0	2717	283	90.57	9.43
50	60	55	283	9.43	3000	283	100	9.43
TOTAL	-	-	3000	100	-	-	-	-
Autor: Grupo 3

#Histograma

hist(Latitud, breaks = 10,
     main = "Gráfica N°49:Distribución para la Latitud (° ′ ″)",
     xlab = "Latitud (° ′ ″)",
     ylab = "Cantidad",
     ylim = c(0, max(ni)),
     col = "purple",
     cex.main = 0.9,
     cex.lab = 1,
     cex.axis = 0.9,
     xaxt = "n")
axis(1, at = hist(Latitud, plot = FALSE)$breaks,
     labels = hist(Latitud, plot = FALSE)$breaks, las = 1,
     cex.axis = 0.9)

#Gráficas

#Gráfica Global ni

hist(Latitud, breaks = 10,
     main = "Gráfica N°50: Distribución para la 
     Latitud",
     xlab = "Latitud (° ′ ″)",
     ylab = "Cantidad",
     ylim = c(0, length(Latitud)),
     col = "green",
     cex.main = 0.9,
     cex.lab = 1,
     cex.axis = 0.9,
     xaxt = "n")
axis(1, at = Hist_Latitud$breaks,
     labels = Hist_Latitud$breaks, las = 1,
     cex.axis = 0.9)

# Gráfica Global hi

datos_grafico <- TDF_Latitud[ !(TDF_Latitud$MC %in% c("-", "TOTAL")), ]

barplot(
  as.numeric(datos_grafico$`hi(%)`),
  space = 0,
  col = "skyblue",
  main = "Gráfica N°51: Distribución porcentual de la Latitud",
  xlab = "Latitud (° ′ ″)",
  ylab = "Porcentaje",
  names.arg = datos_grafico$MC,
  ylim = c(0, 100)
)

# Gráfica Local hi
datos_grafico <- TDF_Latitud[ !(TDF_Latitud$MC %in% c("-", "TOTAL")), ]

barplot(
  as.numeric(datos_grafico$`hi(%)`),
  space = 0,
  col = "red",
  main = "Gráfica N°52: Distribución porcentual de la Latitud",
  xlab = "Latitud (° ′ ″)",
  ylab = "Porcentaje",
  names.arg = datos_grafico$MC,
  ylim = c(0, 40)
)

# Diagrama de Caja

boxplot(Latitud,
        horizontal = TRUE,
        main = "Gráfica N°53:Distribución de la Latitud",
        xlab = "Latitud (° ′ ″)",
        col = "pink",
        outline = TRUE,
        pch = 1)

# Diagrama de Ojiva Ascendente y Descendente

plot(Li ,Ni_desc,
     main = "Gráfica N°54: Distribución Ascendente y descendente 
      para la Latitud (° ′ ″)",
     xlab = "Latitud (° ′ ″)",
     ylab = "Cantidad",
     xlim = c(0,900),
     col = "red",
     cex.axis=0.8,
     type = "o",
     lwd = 3,
     las=1,
     xaxt="n")
lines(Ls,Ni_asc,
      col = "green",
      type = "o",
      lwd = 3)
axis(1, at = seq(0, 900, by = 50))

# Diagrama de Ojiva Ascendente y Descendente Porcentual

plot(Li, Hi_desc * 100,
     main = "Gráfica N°55: Distribución Ascendente y Descendente 
     porcentual para la Latitud (° ′ ″) ",
     xlab = "Latitud (° ′ ″)",
     ylab = "Porcentaje",
     xlim = c(0,900),
     col = "red",
     type = "o",
     lwd = 2,
     xaxt="n")
lines(Ls, Hi_asc * 100,
      col = "blue",
      type = "o",
      lwd = 3)
axis(1, at = seq(0,900,by=50))

# INDICADORES


library(e1071)
library(gt)

# Variable
Latitud <- as.numeric(datos_final$Latitud)

# --- INDICADORES DE TENDENCIA CENTRAL ---

# Media aritmética
media_lat <- round(mean(Latitud, na.rm = TRUE), 2)

# Moda (usando tabla de frecuencias)
Tabla_Lat <- as.data.frame(table(Latitud))
max_frec_lat <- max(Tabla_Lat$Freq)
moda_lat <- Tabla_Lat$Latitud[Tabla_Lat$Freq == max_frec_lat]

# Mediana
mediana_lat <- median(Latitud, na.rm = TRUE)

# --- INDICADORES DE DISPERSIÓN ---

# Varianza
varianza_lat <- var(Latitud, na.rm = TRUE)

# Desviación Estándar
sd_lat <- sd(Latitud, na.rm = TRUE)

# Coeficiente de Variación
cv_lat <- round((sd_lat / media_lat) * 100, 2)

# --- INDICADORES DE FORMA ---

# Asimetría
asimetria_lat <- skewness(Latitud, type = 2, na.rm = TRUE)

# Curtosis
curtosis_lat <- kurtosis(Latitud, na.rm = TRUE)

# --- TABLA RESUMEN FINAL ---

tabla_indicadores_latitud <- data.frame(
  "Variable" = c("Latitud"),
  "Rango" = c(paste0("[", round(min(Latitud, na.rm = TRUE), 2),
                     " ; ", round(max(Latitud, na.rm = TRUE), 2), "]")),
  "X"  = c(media_lat),
  "Me" = c(round(mediana_lat, 2)),
  "Mo" = c(paste(moda_lat, collapse = ", ")),
  "V"  = c(round(varianza_lat, 2)),
  "Sd" = c(round(sd_lat, 2)),
  "Cv" = c(cv_lat),
  "As" = c(round(asimetria_lat, 2)),
  "K"  = c(round(curtosis_lat, 2)),
  "Valores_Atipicos" = "No hay presencia de valores atípicos"
)

tabla_indicadores_latitud_gt <- tabla_indicadores_latitud %>% 
  gt() %>% 
  tab_header(
    title = md("Tabla N°14.1"),
    subtitle = md("*Indicadores estadísticos de la variable Latitud*")
  ) %>% 
  tab_source_note(
    source_note = md("Autor: Grupo 3")
  ) %>% 
  tab_options(
    table.border.top.color = "black",
    table.border.bottom.color = "black",
    table.border.top.style = "solid",
    table.border.bottom.style = "solid",
    column_labels.border.top.color = "black",
    column_labels.border.bottom.color = "black",
    column_labels.border.bottom.width = px(2),
    row.striping.include_table_body = TRUE,
    heading.border.bottom.color = "black",
    heading.border.bottom.width = px(2),
    table_body.hlines.color = "gray",
    table_body.border.bottom.color = "black"
  ) %>% 
  tab_style(
    style = cell_text(weight = "bold"),
    locations = cells_body(
      rows = Variable == "Latitud"
    )
  )

tabla_indicadores_latitud_gt

Tabla N°14.1
Indicadores estadísticos de la variable Latitud
Variable	Rango	X	Me	Mo	V	Sd	Cv	As	K	Valores_Atipicos
Latitud	[-25.27 ; 51.17]	17.46	23.63	35.8617	508.22	22.54	129.12	-0.49	-0.8	No hay presencia de valores atípicos
Autor: Grupo 3