Precipitación

UNIVERSIDAD CENTRAL DEL ECUADOR

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

FECHA: 19/11/2025

# =========================
# ESTADÍSTICA Descriptiva
# Fecha: 19/11/2025
# =========================

# -------------------------
# Cargar datos
# -------------------------

setwd("C:/Users/Alexander/Downloads")

datos <- read.csv("soil_pollution_diseases.csv",
                  sep = ",",
                  stringsAsFactors = FALSE)

# -------------------------
# Variable Cuantitativa Continua
# -------------------------

Precipitacion <- datos$Rainfall_mm

# Número de clases manual
k <- floor(1 + 3.3 * log10(length(Precipitacion)))
min_val <- min(Precipitacion)
max_val <- max(Precipitacion)
R <- max_val - min_val
A <- R / k

Li <- round(seq(from = min_val, to = max_val - A, by = A), 4)
Ls <- round(seq(from = min_val + A, to = max_val, by = A), 4)
MC <- round((Li + Ls) / 2, 2)

ni <- numeric(length(Li))
for (i in 1:length(Li)) {
  if (i < length(Li)) {
    ni[i] <- sum(Precipitacion >= Li[i] & Precipitacion < Ls[i])
  } else {
    ni[i] <- sum(Precipitacion >= Li[i] & Precipitacion <= max_val)
  }
}

hi <- round(ni / sum(ni) * 100, 2)
Niasc <- cumsum(ni)
Nidsc <- rev(cumsum(rev(ni)))
Hiasc <- round(cumsum(hi), 2)
Hidsc <- round(rev(cumsum(rev(hi))), 2)

TDFPrecipitacion <- data.frame(Li, Ls, MC, ni, hi, Niasc, Nidsc, Hiasc, Hidsc)

# Totales
TDFPrecipitacionCompleto <- rbind(
  TDFPrecipitacion,
  data.frame(Li = "Total", Ls = "-", MC = "-", ni = sum(ni), hi = 100,
             Niasc = "-", Nidsc = "-", Hiasc = "-", Hidsc = "-")
)

# Tabla GT
library(gt)
library(dplyr)

tabla_Precipitacion <- TDFPrecipitacionCompleto %>%
  gt() %>%
  fmt_number(
    columns = hi,
    decimals = 2
  ) %>%
  tab_header(
    title = md("*Tabla Nº5*"),
    subtitle = md("**Tabla de Precipitación (mm)**")
  ) %>%
  tab_source_note(
    source_note = md("Autor: Grupo 3")
  ) %>%
  tab_style(
    style = cell_text(weight = "bold"),
    locations = cells_body(rows = Li == "Total")
  )
# Mostrar tabla completa de Precipitación
tabla_Precipitacion

Tabla Nº5
Tabla de Precipitación (mm)
Li	Ls	MC	ni	hi	Niasc	Nidsc	Hiasc	Hidsc
0	33.3083	16.65	238	7.93	238	3000	7.93	99.99
33.3083	66.6167	49.96	251	8.37	489	2762	16.3	92.06
66.6167	99.925	83.27	256	8.53	745	2511	24.83	83.69
99.925	133.2333	116.58	250	8.33	995	2255	33.16	75.16
133.2333	166.5417	149.89	241	8.03	1236	2005	41.19	66.83
166.5417	199.85	183.2	268	8.93	1504	1764	50.12	58.8
199.85	233.1583	216.5	263	8.77	1767	1496	58.89	49.87
233.1583	266.4667	249.81	244	8.13	2011	1233	67.02	41.1
266.4667	299.775	283.12	239	7.97	2250	989	74.99	32.97
299.775	333.0833	316.43	238	7.93	2488	750	82.92	25
333.0833	366.3917	349.74	245	8.17	2733	512	91.09	17.07
366.3917	399.7	383.05	267	8.90	3000	267	99.99	8.9
Total	-	-	3000	100.00	-	-	-	-
Autor: Grupo 3

# Histograma
histoP <- hist(
  Precipitacion,
  main = "Distribución de la Precipitación (mm)",
  xlab = "Precipitación (mm)",
  ylab = "Cantidad",
  col = "blue"
)

# Tabla simplificada basada en el histograma
LimInf <- histoP$breaks[1:(length(histoP$breaks)-1)]
LimSup <- histoP$breaks[2:length(histoP$breaks)]
Mc_hist <- histoP$mids
ni_hist <- histoP$counts
hi_hist <- round(ni_hist / sum(ni_hist) * 100, 2)
hi_hist[length(hi_hist)] <- hi_hist[length(hi_hist)] + (100 - sum(hi_hist))

Ni_asc <- cumsum(ni_hist)
Ni_dsc <- rev(cumsum(rev(ni_hist)))
Hi_asc <- round(cumsum(hi_hist), 2)
Hi_dsc <- round(rev(cumsum(rev(hi_hist))), 2)

TDFP <- data.frame(LimInf, LimSup, Mc = Mc_hist, ni = ni_hist,
                   hi = hi_hist, Ni_asc, Ni_dsc, Hi_asc, Hi_dsc)

TDFPCompleto <- rbind(
  TDFP,
  data.frame(LimInf = "Total", LimSup = "-", Mc = "-", ni = sum(ni_hist),
             hi = 100, Ni_asc = "-", Ni_dsc = "-", Hi_asc = "-", Hi_dsc = "-")
)

tablaPre <- TDFPCompleto %>%
  gt() %>%
  tab_header(
    title = md("*Tabla Nº6*"),
    subtitle = md("**Tabla simplificada de Precipitación (mm)**")
  ) %>%
  tab_source_note(
    source_note = md("Autor: Grupo 3")
  ) %>%
  tab_style(
    style = cell_text(weight = "bold"),
    locations = cells_body(rows = LimInf == "Total")
  )
# Mostrar tabla simplificada basada en el histograma
tablaPre

Tabla Nº6
Tabla simplificada de Precipitación (mm)
LimInf	LimSup	Mc	ni	hi	Ni_asc	Ni_dsc	Hi_asc	Hi_dsc
0	50	25	365	12.17	365	3000	12.17	100
50	100	75	382	12.73	747	2635	24.9	87.83
100	150	125	367	12.23	1114	2253	37.13	75.1
150	200	175	392	13.07	1506	1886	50.2	62.87
200	250	225	385	12.83	1891	1494	63.03	49.8
250	300	275	360	12.00	2251	1109	75.03	36.97
300	350	325	349	11.63	2600	749	86.66	24.97
350	400	375	400	13.34	3000	400	100	13.34
Total	-	-	3000	100.00	-	-	-	-
Autor: Grupo 3

# Graficas
hist(Precipitacion, breaks = seq(min_val, max_val, A),
     main = "Gráfica Nº23: Frecuencia Local de la Precipitación",
     xlab = "Precipitación (mm)", ylab = "Frecuencia",
     col = "#4A90E2")

hist(Precipitacion, breaks = seq(min_val, max_val, A),
     main = "Gráfica Nº24: Frecuencia Global de la Precipitación",
     xlab = "Precipitación (mm)", ylab = "Frecuencia",
     col = "green", ylim = c(0, 3000))

barplot(TDFPrecipitacion$hi,
        space = 0, col = "skyblue",
        main = "Gráfica Nº25: Porcentaje Local de la Precipitación",
        xlab = "Precipitación (mm)", ylab = "Porcentaje (%)",
        names.arg = TDFPrecipitacion$MC, ylim = c(0, max(TDFPrecipitacion$hi)))

barplot(TDFPrecipitacion$hi,
        space = 0, col = "yellow",
        main = "Gráfica Nº26: Porcentaje Global de la Precipitación",
        xlab = "Precipitación (mm)", ylab = "Porcentaje (%)",
        names.arg = TDFPrecipitacion$MC, ylim = c(0, 100))

boxplot(Precipitacion,
        horizontal = TRUE, col = "pink",
        main = "Gráfica Nº27: Distribución de la Precipitación (mm)",
        xlab = "Precipitación (mm)")

# Ojivas
plot(Li, Nidsc, type = "o", col = "red", lwd = 3,
     main = "Gráfica Nº28: Frecuencia Ascendente y Descendente",
     xlab = "Precipitación (mm)", ylab = "Cantidad", xaxt = "n")
lines(Ls, Niasc, type = "o", col = "green", lwd = 3)
axis(1, at = round(seq(min_val, max_val, length.out = 10), 0))

plot(Li, Hidsc, type = "o", col = "red", lwd = 2,
     main = "Gráfica Nº29: Distribución Porcentual Ascendente y Descendente",
     xlab = "Precipitación (mm)", ylab = "Porcentaje (%)", xaxt = "n")
lines(Ls, Hiasc, type = "o", col = "blue", lwd = 3)
axis(1, at = round(seq(min_val, max_val, length.out = 10), 0))

# INDICADORES ESTADISTICOS
media <- round(mean(Precipitacion), 2)
mediana <- round(median(Precipitacion), 2)
Tabla_Prec <- as.data.frame(table(Precipitacion))
moda <- as.numeric(names(Tabla_Prec)[Tabla_Prec$Freq == max(Tabla_Prec$Freq)])
varianza <- round(var(Precipitacion), 2)
desviacion <- round(sd(Precipitacion), 2)
cv <- round((desviacion / media) * 100, 2)
library(e1071)
asimetria <- round(skewness(Precipitacion, type = 2), 2)
curtosis <- round(kurtosis(Precipitacion), 2)

# Tabla resumen indicadores
tabla_indicadores <- data.frame(
  Variable = "Precipitación",
  Rango = paste0("[", min_val, " ; ", max_val, "]"),
  X = media,
  Me = mediana,
  Mo = paste(moda, collapse = ", "),
  V = varianza,
  Sd = desviacion,
  Cv = cv,
  As = asimetria,
  K = curtosis,
  Valores_Atipicos = "No hay valores atípicos"
)

tabla_indicadores_gt <- tabla_indicadores %>%
  gt() %>%
  tab_header(
    title = md("*Tabla N°7*"),
    subtitle = md("**Indicadores Estadísticos de Precipitación (mm)**")
  ) %>%
  tab_source_note(source_note = md("Autor: Grupo 3"))
# Mostrar tabla de indicadores estadísticos
tabla_indicadores_gt

Tabla N°7
Indicadores Estadísticos de Precipitación (mm)
Variable	Rango	X	Me	Mo	V	Sd	Cv	As	K	Valores_Atipicos
Precipitación	[0 ; 399.7]	200.32	199	NA	13287.6	115.27	57.54	0.01	-1.19	No hay valores atípicos
Autor: Grupo 3

##============##
## CONCLUSION ##
##============##
# La variable Precipitación fluctua entre 0 y 399.7 y gira entorno a 200.32 con una desviación estandar de 115.27 siendo un conjuto de datos heterogeneo, los valores de acumulan de manera debil en la parte media de la variable. Sin presencia de valores atípicos.