Variables Discretas
Braider Albuja
2025-06-06
library(e1071) Cargar los datos
setwd("D:/Data")
datos <- read.csv("database.csv", header = TRUE, sep = ";", dec =".")Variable: Cilindros del motor
cilindros_m <- datos$Engine.Cylinders
cilindros_m <- as.character(datos$Engine.Cylinders)
cilindros_m <- gsub("[^0-9]", "", cilindros_m)
cilindros_m <- as.numeric(cilindros_m)
cilindros_m <- cilindros_m[!is.na(cilindros_m) & cilindros_m >= 2 & cilindros_m <= 16]
TDF_cilindros <- table(cilindros_m)
Tabla_cilindros <- as.data.frame(TDF_cilindros)
colnames(Tabla_cilindros) <- c("CILINDROS", "Freq")
hi <- (Tabla_cilindros$Freq / sum(Tabla_cilindros$Freq)) * 100
Niasc <- cumsum(Tabla_cilindros$Freq)
Hiasc <- cumsum(hi)
Nidsc <- rev(cumsum(rev(Tabla_cilindros$Freq)))
Hidsc <- rev(cumsum(rev(hi)))
#Tabla
Tabla_cilindrosFinal <- data.frame(
CILINDROS = Tabla_cilindros$CILINDROS,
Freq = Tabla_cilindros$Freq,
hi_perc = round(hi, 2),
Niasc = Niasc,
Hiasc_perc = round(Hiasc, 2),
Nidsc = Nidsc,
Hidsc_perc = round(Hidsc, 2)
)Tabla
print(Tabla_cilindrosFinal)## CILINDROS Freq hi_perc Niasc Hiasc_perc Nidsc Hidsc_perc
## 1 2 43 0.12 43 0.12 35599 100.00
## 2 3 197 0.55 240 0.67 35556 99.88
## 3 4 13522 37.98 13762 38.66 35359 99.33
## 4 5 703 1.97 14465 40.63 21837 61.34
## 5 6 12733 35.77 27198 76.40 21134 59.37
## 6 7 12 0.03 27210 76.43 8401 23.60
## 7 8 7677 21.57 34887 98.00 8389 23.57
## 8 10 145 0.41 35032 98.41 712 2.00
## 9 12 559 1.57 35591 99.98 567 1.59
## 10 16 8 0.02 35599 100.00 8 0.02GRÁFICA 1.1: DISTRIBUCIÓN DE CILINDROS DEL MOTOR LOCAL
barplot(Tabla_cilindrosFinal$Freq,
main = "GRÁFICA NO.1: DISTRIBUCIÓN DE CILINDROS DEL MOTOR",
xlab = "CILINDROS DEL MOTOR",
ylab = "CANTIDAD",
col = "skyblue",
names.arg = Tabla_cilindrosFinal$CILINDROS)
GRÁFICA 1.2: DISTRIBUCIÓN DE CILINDROS DEL MOTOR GLOBAL
barplot(Tabla_cilindrosFinal$Freq,
main = "GRÁFICA NO.2: DISTRIBUCIÓN DE CILINDROS DEL MOTOR",
xlab = "CILINDROS DEL MOTOR",
ylab = "CANTIDAD",
col = "blue",
names.arg = Tabla_cilindrosFinal$CILINDROS,
ylim = c(0, sum(Tabla_cilindrosFinal$Freq)))
GRÁFICA 1.3: DISTRIBUCIÓN DE CILINDROS DEL MOTOR PORCENTUAL
barplot(Tabla_cilindrosFinal$hi_perc,
main = "GRÁFICA NO.3: FRECUENCIA DE CILINDROS DEL MOTOR (%)",
xlab = "CILINDROS DEL MOTOR",
ylab = "PORCENTAJE",
col = "azure",
names.arg = Tabla_cilindrosFinal$CILINDROS,
ylim = c(0, 100))
GRÁFICA 1.4: DISTRIBUCIÓN DE CILINDROS DEL MOTOR BOXPLOT
boxplot(cilindros_m,
horizontal = TRUE,
col = "lightblue",
main = "GRÁFICA NO.4: BOXPLOT DE CILINDROS DEL MOTOR",
xlab = "NÚMERO DE CILINDROS")
GRÁFICA 1.5: DISTRIBUCIÓN DE CILINDROS DEL MOTOR OJIVA ASCENDENTE
x_ojiva_asc <- as.numeric(as.character(Tabla_cilindrosFinal$CILINDROS))
y_ojiva_asc <- Tabla_cilindrosFinal$Niasc
plot(x_ojiva_asc, y_ojiva_asc,
type = "o",
main = "GRÁFICA NO.5: OJIVA ASCENDENTE DE CILINDROS",
xlab = "NÚMERO DE CILINDROS",
ylab = "CANTIDAD ACUMULADA",
col = "orange",
pch = 16)
GRÁFICA 1.6: DISTRIBUCIÓN DE CILINDROS DEL MOTOR OJIVA DESCENDENTE
x_ojiva_desc <- as.numeric(as.character(Tabla_cilindrosFinal$CILINDROS))
y_ojiva_desc <- Tabla_cilindrosFinal$Nidsc
plot(x_ojiva_desc, y_ojiva_desc,
type = "o",
main = "GRÁFICA NO.6: OJIVA DESCENDENTE DE CILINDROS",
xlab = "NÚMERO DE CILINDROS",
ylab = "CANTIDAD ACUMULADA",
col = "green",
pch = 16)
GRÁFICA 1.7: DISTRIBUCIÓN DE CILINDROS DEL MOTOR OJIVA
plot(x_ojiva_asc, y_ojiva_asc,
type = "o",
main = "GRÁFICA NO.7: OJIVAS DE CILINDROS DEL MOTOR",
xlab = "NÚMERO DE CILINDROS",
ylab = "CANTIDAD ACUMULADA",
col = "orange",
pch = 16)
lines(x_ojiva_desc, y_ojiva_desc, type = "o", col = "green", pch = 16)
Indicadores estadísticos
get_mode <- function(x) {
ux <- unique(x)
ux[which.max(tabulate(match(x, ux)))]
}
mean_cil <- mean(cilindros_m)
median_cil <- median(cilindros_m)
sd_cil <- sd(cilindros_m)
indicadores_cilindros <- data.frame(
Indicador = c("Moda", "Mediana", "Media (x̄)", "Desviación Estándar (σ)",
"Varianza (σ²)", "Coef. Variación (%)", "Asimetría", "Curtosis"),
Valor = c(
round(get_mode(cilindros_m), 2),
round(median_cil, 2),
round(mean_cil, 2),
round(sd_cil, 2),
round(var(cilindros_m), 2),
round((sd_cil / mean_cil) * 100, 2),
round(skewness(cilindros_m), 2),
round(kurtosis(cilindros_m), 2)
)
)
boxplot.stats(cilindros_m)$out## [1] 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12
## [26] 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 10 12
## [51] 12 12 12 12 12 12 12 12 12 12 12 12 12 10 12 12 12 12 12 12 12 12 12 12 12
## [76] 10 12 12 12 12 12 12 12 12 12 12 10 12 12 12 12 12 12 12 12 12 12 12 12 12
## [101] 10 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 10 10 12 12 12 12 12 12
## [126] 12 12 10 10 12 12 12 12 12 12 12 12 12 12 12 12 12 10 10 12 12 12 12 12 10
## [151] 10 12 12 12 12 12 12 12 12 12 12 10 10 12 12 12 12 12 12 12 12 12 12 12 12
## [176] 12 12 12 12 12 12 12 12 12 10 12 12 12 12 12 12 12 12 12 12 12 12 12 10 10
## [201] 12 12 10 10 12 12 12 12 12 12 12 10 12 12 10 12 12 12 12 12 12 12 12 12 10
## [226] 10 10 12 12 12 12 10 10 12 12 12 12 12 12 12 12 12 10 12 12 12 12 12 12 12
## [251] 12 12 12 12 12 10 10 16 10 10 10 12 12 12 12 10 10 10 10 12 12 12 12 12 12
## [276] 12 12 12 12 12 12 12 10 12 12 12 12 12 10 10 12 12 12 12 10 10 10 10 10 10
## [301] 12 12 12 12 10 10 10 10 10 10 12 12 12 12 12 12 12 12 12 12 12 12 12 10 12
## [326] 12 12 12 12 10 10 12 12 12 12 10 10 10 10 10 10 16 10 10 12 12 12 12 10 10
## [351] 10 10 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 10 12 12 12 12
## [376] 12 10 10 12 12 12 10 10 10 10 10 10 10 10 12 12 12 12 10 10 10 10 12 12 12
## [401] 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 10 10 10 12 12
## [426] 12 12 12 10 10 10 10 10 10 16 10 10 12 12 12 12 10 10 10 10 12 12 12 12 12
## [451] 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 10 10 10 10 10 12 12
## [476] 12 12 12 16 12 12 12 12 12 12 10 10 10 10 12 12 12 12 12 12 12 12 12 12 12
## [501] 12 12 12 12 12 12 12 12 12 12 12 10 10 10 10 12 12 12 12 12 12 16 12 12 10
## [526] 10 10 10 10 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12
## [551] 12 12 12 16 12 12 12 10 10 10 10 12 12 12 12 12 12 12 12 12 12 12 10 12 12
## [576] 12 12 10 10 10 10 12 12 12 12 12 16 12 12 12 12 12 12 10 10 10 10 12 12 12
## [601] 12 12 12 12 12 12 12 12 10 12 12 12 12 12 10 10 10 10 12 12 12 12 16 10 12
## [626] 12 12 12 10 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 10
## [651] 12 12 12 12 12 12 10 10 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12
## [676] 12 12 10 10 12 12 12 12 12 10 12 12 12 12 12 12 12 12 10 10 10 10 12 12 12
## [701] 12 12 12 12 12 12 12 12 12 12 12 12length(boxplot.stats(cilindros_m)$out)## [1] 712outliers <- boxplot.stats(cilindros_m)$out
range(outliers)## [1] 10 16Tabla indicadores estadisticos
cat("Tabla de Indicadores: Número de Cilindros del Motor\n")## Tabla de Indicadores: Número de Cilindros del Motorprint(indicadores_cilindros)## Indicador Valor
## 1 Moda 4.00
## 2 Mediana 6.00
## 3 Media (x̄) 5.74
## 4 Desviación Estándar (σ) 1.75
## 5 Varianza (σ²) 3.06
## 6 Coef. Variación (%) 30.45
## 7 Asimetría 0.88
## 8 Curtosis 1.01Conclusiones
El comportamiento de la variable de los cilindros del motor fluctúa entre [2-16] y los valores se encuentran en torno a la mediana de 6, con una desviación estándar de 1.75, siendo un conjunto con un coeficiente de variación hetergogéneo y tiene un sesgo positivo con existencia de valores atípicos a partir de 10 cilindros.
Variable: PUNTUACIÓN DE ECONOMIA DE COMBUSTIBLE
puntuacion_c <- datos$Fuel.Economy.Score
puntuacion_c <- as.character(puntuacion_c)
puntuacion_c <- gsub("[^0-9]", "", puntuacion_c)
puntuacion_c <- as.numeric(puntuacion_c)
puntuacion_c <- puntuacion_c[!is.na(puntuacion_c) & puntuacion_c >= 0 & puntuacion_c <= 100] # Ajusta si el rango esperado es distinto
TDF_puntuacion <- table(puntuacion_c)
Tabla_puntuacion <- as.data.frame(TDF_puntuacion)
colnames(Tabla_puntuacion) <- c("PUNTUACION", "Freq")
hi <- (Tabla_puntuacion$Freq / sum(Tabla_puntuacion$Freq)) * 100
Niasc <- cumsum(Tabla_puntuacion$Freq)
Hiasc <- cumsum(hi)
Nidsc <- rev(cumsum(rev(Tabla_puntuacion$Freq)))
Hidsc <- rev(cumsum(rev(hi)))
# Tabla
Tabla_puntuacionFinal <- data.frame(
PUNTUACION = Tabla_puntuacion$PUNTUACION,
Freq = Tabla_puntuacion$Freq,
hi_perc = round(hi, 2),
Niasc = Niasc,
Hiasc_perc = round(Hiasc, 2),
Nidsc = Nidsc,
Hidsc_perc = round(Hidsc, 2)
)Tabla
print(Tabla_puntuacionFinal)## PUNTUACION Freq hi_perc Niasc Hiasc_perc Nidsc Hidsc_perc
## 1 0 1790 4.77 1790 4.77 37515 100.00
## 2 1 30129 80.31 31919 85.08 35725 95.23
## 3 2 245 0.65 32164 85.74 5596 14.92
## 4 3 474 1.26 32638 87.00 5351 14.26
## 5 4 1038 2.77 33676 89.77 4877 13.00
## 6 5 1478 3.94 35154 93.71 3839 10.23
## 7 6 902 2.40 36056 96.11 2361 6.29
## 8 7 777 2.07 36833 98.18 1459 3.89
## 9 8 432 1.15 37265 99.33 682 1.82
## 10 9 90 0.24 37355 99.57 250 0.67
## 11 10 160 0.43 37515 100.00 160 0.43GRÁFICA 2.1: DISTRIBUCIÓN DE PUNTUACION DE ECONOMIA LOCAL
barplot(Tabla_puntuacionFinal$Freq,
main = "GRÁFICA NO.1: DISTRIBUCIÓN DE PUNTUACIÓN DE ECONOMÍA",
xlab = "PUNTUACIÓN",
ylab = "CANTIDAD",
col = "skyblue",
names.arg = Tabla_puntuacionFinal$PUNTUACION)
GRÁFICA 2.2: DISTRIBUCIÓN DE PUNTUACION DE ECONOMIA GLOBAL
barplot(Tabla_puntuacionFinal$Freq,
main = "GRÁFICA NO.2: DISTRIBUCIÓN DE PUNTUACIÓN DE ECONOMÍA",
xlab = "PUNTUACIÓN",
ylab = "CANTIDAD",
col = "blue",
names.arg = Tabla_puntuacionFinal$PUNTUACION,
ylim = c(0, sum(Tabla_puntuacionFinal$Freq)))
GRÁFICA 2.3: FRECUENCIA DE PUNTUACION DE ECONOMIA PORCENTUAL
barplot(Tabla_puntuacionFinal$hi_perc,
main = "GRÁFICA NO.3: FRECUENCIA DE PUNTUACIÓN DE ECONOMÍA (%)",
xlab = "PUNTUACIÓN",
ylab = "PORCENTAJE",
col = "azure",
names.arg = Tabla_puntuacionFinal$PUNTUACION,
ylim = c(0, 100))
GRÁFICA 2.4: DISTRIBUCIÓN DE PUNTUACION DE ECONOMIA BOXPLOT
boxplot(puntuacion_c,
horizontal = TRUE,
col = "lightblue",
main = "GRÁFICA NO.4: BOXPLOT DE PUNTUACIÓN DE ECONOMÍA",
xlab = "PUNTUACIÓN")
GRÁFICA 2.5: DISTRIBUCIÓN DE PUNTUACION DE ECONOMIA OJIVA ASCENDENTE
x_ojiva_asc <- as.numeric(as.character(Tabla_puntuacionFinal$PUNTUACION))
y_ojiva_asc <- Tabla_puntuacionFinal$Niasc
plot(x_ojiva_asc, y_ojiva_asc,
type = "o",
main = "GRÁFICA NO.5: OJIVA ASCENDENTE DE PUNTUACIÓN DE ECONOMÍA",
xlab = "PUNTUACIÓN",
ylab = "CANTIDAD ACUMULADA",
col = "orange",
pch = 16)
GRÁFICA 2.6: DISTRIBUCIÓN DE PUNTUACION DE ECONOMIA OJIVA DESCENDENTE
x_ojiva_desc <- as.numeric(as.character(Tabla_puntuacionFinal$PUNTUACION))
y_ojiva_desc <- Tabla_puntuacionFinal$Nidsc
plot(x_ojiva_desc, y_ojiva_desc,
type = "o",
main = "GRÁFICA NO.6: OJIVA DESCENDENTE DE PUNTUACIÓN DE ECONOMÍA",
xlab = "PUNTUACIÓN",
ylab = "CANTIDAD ACUMULADA",
col = "green",
pch = 16)
GRÁFICA 2.7: DISTRIBUCIÓN DE PUNTUACION DE ECONOMIA OJIVAS
plot(x_ojiva_asc, y_ojiva_asc,
type = "o",
main = "GRÁFICA NO.7: OJIVAS DE PUNTUACIÓN DE ECONOMÍA",
xlab = "PUNTUACIÓN",
ylab = "CANTIDAD ACUMULADA",
col = "orange",
pch = 16)
lines(x_ojiva_desc, y_ojiva_desc, type = "o", col = "green", pch = 16)
Indicadores estadisticos
get_mode <- function(x) {
ux <- unique(x)
ux[which.max(tabulate(match(x, ux)))]
}
mean_p <- mean(puntuacion_c)
median_p <- median(puntuacion_c)
sd_p <- sd(puntuacion_c)
indicadores_puntuacion <- data.frame(
Indicador = c("Moda", "Mediana", "Media (x̄)", "Desviación Estándar (σ)",
"Varianza (σ²)", "Coef. Variación (%)", "Asimetría", "Curtosis"),
Valor = c(
round(get_mode(puntuacion_c), 2),
round(median_p, 2),
round(mean_p, 2),
round(sd_p, 2),
round(var(puntuacion_c), 2),
round((sd_p / mean_p) * 100, 2),
round(skewness(puntuacion_c), 2),
round(kurtosis(puntuacion_c), 2)
)
)
# Outliers
boxplot.stats(puntuacion_c)$out## [1] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## [25] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## [49] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## [73] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## [97] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## [121] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## [145] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## [169] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## [193] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## [217] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## [241] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## [265] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## [289] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## [313] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## [337] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## [361] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## [385] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## [409] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## [433] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## [457] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## [481] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## [505] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## [529] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## [553] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## [577] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## [601] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## [625] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## [649] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## [673] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## [697] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## [721] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## [745] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## [769] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## [793] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## [817] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## [841] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## [865] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## [889] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## [913] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## [937] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## [961] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## [985] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## [1009] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## [1033] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## [1057] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## [1081] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## [1105] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## [1129] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## [1153] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## [1177] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## [1201] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## [1225] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## [1249] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## [1273] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## [1297] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## [1321] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## [1345] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## [1369] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## [1393] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## [1417] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## [1441] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## [1465] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## [1489] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## [1513] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## [1537] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## [1561] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## [1585] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## [1609] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## [1633] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## [1657] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## [1681] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## [1705] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## [1729] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## [1753] 0 0 0 0 7 6 9 4 6 5 6 5 5 7 6 6 6 4 3 3 3 3 3 6
## [1777] 6 6 7 6 7 7 6 6 7 7 6 5 5 5 5 5 4 3 6 6 5 7 4 4
## [1801] 4 5 5 5 5 5 5 5 4 7 7 5 2 2 4 3 2 4 3 2 2 5 5 5
## [1825] 5 5 6 5 5 7 7 7 7 7 7 5 5 5 5 5 4 7 7 6 5 5 5 5
## [1849] 5 6 6 6 4 5 4 5 7 7 6 6 6 6 5 5 4 4 4 4 6 7 6 4
## [1873] 4 4 4 4 4 5 5 5 4 4 4 4 3 7 7 6 4 4 4 4 3 3 3 3
## [1897] 3 4 3 4 3 4 3 4 7 7 5 6 5 2 5 4 3 2 4 3 7 7 4 5
## [1921] 4 4 4 7 7 5 8 6 5 5 8 6 6 10 7 5 6 6 5 6 2 5 5 3
## [1945] 4 5 5 2 5 5 3 5 5 3 3 3 2 2 5 5 5 5 4 4 4 4 2 4
## [1969] 5 5 3 4 5 4 4 4 4 8 7 8 8 8 8 6 4 7 5 0 5 7 6 8
## [1993] 5 5 4 3 4 2 4 3 3 4 2 8 7 8 8 8 7 8 8 7 8 8 9 4
## [2017] 4 4 4 5 5 4 4 10 6 5 6 4 6 6 5 5 4 5 5 4 5 10 6 5
## [2041] 6 4 5 4 4 4 4 5 5 6 6 4 5 5 4 8 7 7 6 8 8 7 8 8
## [2065] 4 3 4 3 5 5 4 5 5 3 2 8 8 9 8 10 10 10 0 0 5 4 5 5
## [2089] 5 6 6 6 6 6 7 3 3 5 4 4 4 5 6 3 4 4 4 4 4 4 2 4
## [2113] 4 3 4 3 4 2 8 8 8 4 4 5 10 8 8 8 7 6 10 7 7 7 8 10
## [2137] 6 5 5 4 6 5 5 5 6 7 6 6 6 4 4 0 5 5 4 3 4 2 4 3
## [2161] 3 4 2 2 6 4 3 4 5 5 3 5 4 3 4 2 8 6 8 6 7 5 8 8
## [2185] 6 8 10 8 7 6 9 9 6 6 5 8 8 8 10 10 10 5 5 5 5 4 8 8
## [2209] 6 8 8 8 8 8 8 8 4 5 5 4 6 5 4 5 5 6 6 5 5 7 7 7
## [2233] 9 9 6 6 5 6 6 5 8 7 8 7 5 5 4 4 3 5 5 5 4 5 5 5
## [2257] 5 5 5 8 5 5 4 4 3 3 5 4 6 4 4 5 4 4 4 5 4 4 4 4
## [2281] 4 6 6 6 7 5 6 6 4 3 4 3 2 6 6 6 7 5 6 6 4 4 4 4
## [2305] 8 7 8 7 8 8 7 7 7 7 7 7 9 9 8 8 8 6 6 5 5 5 6 5
## [2329] 7 6 7 7 7 7 6 6 6 6 5 5 2 3 3 3 2 5 2 3 3 6 2 3
## [2353] 10 10 6 6 5 8 4 6 6 5 5 4 4 4 4 4 5 2 5 5 5 8 8 5
## [2377] 5 5 4 5 4 6 4 5 6 5 7 5 9 3 3 6 5 5 5 3 3 2 8 8
## [2401] 7 6 7 6 6 6 6 5 6 8 8 8 8 8 8 7 4 4 6 6 6 5 6 6
## [2425] 5 6 5 6 3 3 3 4 2 4 2 5 4 4 6 5 5 5 6 5 6 7 5 4
## [2449] 5 4 4 2 2 5 3 3 2 7 5 5 5 5 6 3 3 4 6 5 4 4 2 4
## [2473] 2 5 4 4 7 7 6 5 3 3 3 3 8 8 8 8 8 8 8 8 7 8 7 8
## [2497] 8 8 8 8 8 8 8 8 8 8 7 8 7 7 7 8 7 7 8 8 8 8 7 7
## [2521] 7 7 8 8 8 8 8 8 8 8 8 8 8 10 5 8 7 7 7 6 4 4 7 6
## [2545] 6 5 6 5 7 7 7 5 5 5 5 8 6 7 3 3 2 2 7 7 4 4 5 4
## [2569] 4 4 4 8 7 7 10 5 5 4 5 0 5 5 5 6 6 9 8 8 9 3 3 2
## [2593] 2 9 8 8 4 4 4 6 5 6 5 5 5 5 5 5 5 6 5 5 5 5 5 4
## [2617] 4 4 4 4 4 7 6 6 6 4 4 4 4 5 4 5 5 4 4 4 6 4 4 3
## [2641] 3 5 5 4 3 3 4 4 5 5 3 3 2 2 2 2 4 4 7 6 9 10 7 7
## [2665] 6 6 8 8 9 9 10 10 3 7 6 6 5 6 8 5 7 4 8 5 7 4 5 7
## [2689] 6 5 7 6 4 7 7 5 5 5 7 6 6 6 6 7 6 6 6 7 7 7 7 10
## [2713] 10 10 4 4 4 6 6 10 7 6 10 10 8 8 4 3 4 5 5 4 7 3 5 6
## [2737] 7 8 6 10 10 10 10 7 6 10 6 3 2 2 5 5 4 5 4 6 4 4 4 4
## [2761] 4 4 4 3 3 3 3 6 5 5 5 8 8 6 6 6 6 6 6 6 6 5 6 5
## [2785] 6 7 7 5 7 6 7 6 7 7 7 7 10 7 7 6 6 7 5 6 5 6 4 5
## [2809] 6 6 5 5 6 6 5 6 5 5 5 5 5 5 4 4 3 7 6 9 6 5 6 5
## [2833] 6 8 6 5 5 7 6 6 6 2 2 3 2 3 2 2 7 7 7 7 7 5 6 5
## [2857] 5 5 4 5 3 5 7 4 3 3 2 2 3 3 2 2 4 4 4 5 5 5 5 5
## [2881] 5 5 4 4 7 7 2 4 2 2 3 2 7 7 7 7 7 9 9 9 7 7 7 7
## [2905] 7 6 6 6 6 6 7 7 7 6 7 6 6 6 6 6 7 7 8 8 6 6 5 6
## [2929] 5 5 4 4 4 6 6 6 6 6 6 5 5 5 4 4 4 5 5 5 5 4 4 4
## [2953] 2 7 7 6 4 4 4 4 10 10 6 6 3 3 3 3 3 3 3 3 7 7 5 6
## [2977] 5 5 7 5 3 2 5 3 7 7 5 5 5 4 4 7 7 5 7 6 6 6 5 7
## [3001] 6 6 6 10 7 6 5 6 5 6 5 2 3 5 6 5 4 5 5 2 3 5 5 2
## [3025] 3 5 5 10 3 2 3 2 4 4 5 5 4 3 3 4 5 2 5 5 4 3 2 5
## [3049] 5 8 8 7 7 8 8 8 4 6 5 7 0 0 0 6 5 7 6 7 7 3 7 8
## [3073] 8 8 7 8 8 8 7 8 7 8 8 8 10 3 3 3 3 3 4 4 10 6 6 5
## [3097] 4 6 6 5 5 4 5 5 3 5 5 6 6 5 5 4 4 3 3 5 5 4 6 6
## [3121] 4 5 5 3 8 7 7 7 7 8 8 7 7 4 3 5 3 5 5 4 5 4 2 2
## [3145] 2 2 2 8 8 8 8 7 7 10 10 9 0 0 5 4 5 5 6 6 6 7 6 6
## [3169] 3 2 5 4 4 4 5 6 4 2 4 4 3 4 3 3 3 4 3 4 3 8 8 8
## [3193] 9 7 4 4 5 10 8 8 8 7 6 10 7 7 7 7 9 6 5 5 4 4 6 5
## [3217] 5 5 7 6 6 6 6 6 6 6 4 4 0 0 0 3 3 4 6 5 7 3 3 2
## [3241] 3 3 3 3 2 7 6 8 7 5 7 10 10 8 8 8 6 9 10 8 7 6 9 8
## [3265] 6 6 5 10 9 9 5 5 5 3 8 8 6 8 7 8 7 7 7 7 8 4 5 5
## [3289] 4 5 4 4 5 5 6 5 5 5 5 4 7 6 9 9 6 6 5 6 8 7 7 8
## [3313] 6 5 8 8 6 5 8 7 5 5 4 5 5 4 5 4 5 8 5 5 5 5 7 7
## [3337] 3 4 4 3 3 6 5 4 6 4 4 4 4 4 4 4 4 4 3 6 5 6 5 5
## [3361] 6 5 5 5 6 6 6 6 6 6 7 5 3 4 3 2 5 6 6 6 6 6 6 7
## [3385] 4 4 4 4 5 7 7 7 7 6 7 6 7 7 6 7 6 7 6 7 9 9 8 8
## [3409] 8 5 5 5 5 5 5 7 7 7 7 6 6 5 5 3 2 3 2 5 3 4 2 6
## [3433] 4 3 9 9 6 6 5 8 3 6 6 6 5 5 5 4 4 4 4 4 5 2 5 5
## [3457] 5 8 7 5 5 5 4 5 4 6 4 5 6 5 7 5 9 3 2 5 5 5 5 4
## [3481] 4 3 2 3 4 8 8 6 6 8 7 8 8 8 8 8 8 7 7 7 7 7 4 4
## [3505] 6 6 6 4 4 3 10 6 6 5 6 5 6 2 2 4 2 4 2 8 7 7 5 4
## [3529] 4 4 4 4 8 8 6 5 6 5 6 7 5 5 5 4 4 3 4 4 4 5 3 2
## [3553] 2 7 5 5 5 4 6 3 2 5 4 4 5 4 3 7 7 6 5 2 2 2 2 2
## [3577] 8 8 8 8 8 8 8 8 7 8 8 8 7 8 8 8 8 7 8 8 8 8 7 7
## [3601] 7 7 8 8 7 7 7 7 8 8 7 7 7 7 8 8 8 8 8 8 8 8 10 5
## [3625] 7 7 7 7 6 4 4 7 6 9 9 7 7 6 7 7 7 2 5 5 5 5 6 8
## [3649] 2 2 2 2 7 7 4 4 5 4 3 4 4 7 7 7 10 5 5 4 5 6 5 5
## [3673] 7 7 5 7 7 6 6 8 8 8 8 2 2 2 2 9 8 8 4 3 3 6 5 6
## [3697] 5 5 5 5 5 5 5 6 5 5 5 5 5 3 5 5 5 5 5 5 5 5 7 6
## [3721] 6 6 5 3 3 4 5 3 3 7 6 6 6 5 5 5 5 4 5 8 4 4 4 4
## [3745] 3 3 5 5 2 4 4 3 5 5 5 2 2 2 2 2 2 2 3 3 7 6 9 7
## [3769] 7 6 6 7 7 9 9 10 10 2 7 6 7 6 6 8 5 7 4 8 5 7 4 5
## [3793] 7 6 5 7 6 4 7 7 8 10 10 10 4 4 4 6 6 9 7 6 9 9 8 8
## [3817] 8 8 9 8 4 3 4 5 5 5 7 7 2 10 10 10 9 7 6 10 6 2 2 2
## [3841] 5 4 5 4 6 4 4 4 4 3 3 3 2 3 2 2 6 5 5 5 8 8 7 6
## [3865] 7 6 7 7 6 6 7 7 6 6 5 6 7 7 6 7 7 6 8 7 7 10 7 7
## [3889] 6 7 6 7 7 5 6 5 6 4 5 5 6 6 5 6 5 5 5 5 5 5 4 4
## [3913] 7 6 5 5 5 5 6 7 6 6 7 3 4 2 3 3 3 3 3 3 3 7 8 7
## [3937] 6 7 7 6 6 7 5 5 5 5 5 5 4 5 5 5 5 6 4 4 3 2 2 4
## [3961] 3 2 2 4 4 4 6 5 5 5 5 5 5 5 5 4 6 6 4 3 4 3 4 4
## [3985] 3 7 6 7 7 6 7 7 7 9 8 8 7 6 6 6 6 6 6 6 5 6 7 7
## [4009] 6 7 6 6 6 6 6 6 6 5 6 5 6 7 6 7 7 6 5 5 5 5 4 4
## [4033] 4 6 6 6 5 5 5 5 5 5 4 4 4 5 6 5 5 5 4 4 4 3 7 6
## [4057] 6 4 4 4 4 4 10 10 6 5 6 5 6 4 5 4 5 4 5 3 4 3 4 3
## [4081] 4 3 4 7 6 5 6 7 6 5 5 5 3 5 7 5 4 3 5 5 4 6 6 5
## [4105] 5 4 4 7 6 5 7 6 5 6 5 7 6 6 6 5 6 6 5 5 5 2 3 6
## [4129] 4 5 5 5 10 4 4 3 4 4 4 3 3 4 4 5 4 5 4 4 4 5 2 5
## [4153] 3 5 4 3 6 5 5 5 5 5 3 5 5 7 7 8 7 7 8 8 4 5 5 6
## [4177] 0 0 0 0 0 5 6 5 7 6 4 4 4 4 4 4 8 7 7 8 8 7 7 8
## [4201] 7 7 7 7 8 8 10 4 4 4 4 4 4 4 4 7 7 10 7 5 7 5 5 4
## [4225] 5 5 5 5 5 5 5 4 5 4 4 4 4 3 4 3 5 4 5 5 5 4 3 8
## [4249] 7 7 7 7 8 8 6 7 4 3 5 4 5 5 4 5 4 3 2 2 2 2 4 7
## [4273] 7 8 7 7 7 7 6 7 10 10 9 5 5 5 6 5 5 6 5 6 6 6 4 4
## [4297] 4 3 5 4 4 4 5 5 5 5 4 5 5 4 4 4 8 8 8 7 4 4 5 10
## [4321] 8 7 7 6 6 10 6 6 7 9 6 5 4 5 4 6 4 6 5 5 5 6 5 5
## [4345] 6 6 5 6 5 0 4 4 5 5 5 5 5 3 0 0 0 0 0 4 4 4 4 4
## [4369] 4 4 5 5 6 4 4 4 4 4 4 3 4 4 3 4 3 7 6 8 6 5 7 10
## [4393] 8 8 8 6 8 10 8 7 7 9 8 5 6 5 8 8 8 5 5 5 7 8 5 5
## [4417] 7 8 7 8 7 7 7 7 8 4 4 4 4 5 4 5 5 5 5 5 5 5 4 5
## [4441] 8 7 6 9 9 6 7 6 6 5 5 7 7 7 7 5 5 5 5 8 7 5 5 7
## [4465] 7 5 5 5 5 4 4 5 4 5 8 5 5 5 5 6 6 4 4 3 3 5 5 4
## [4489] 5 5 4 4 5 5 5 4 4 4 4 4 4 4 4 6 5 6 5 5 6 6 6 5
## [4513] 5 5 5 6 6 5 6 6 5 4 4 3 3 5 5 6 6 5 6 6 6 7 6 7
## [4537] 4 4 4 4 5 7 8 7 7 6 6 7 6 7 6 5 4 6 7 9 9 8 8 8
## [4561] 5 5 4 5 5 5 5 6 6 6 7 10 5 5 6 5 5 5 3 5 5 3 4 6
## [4585] 4 3 4 9 9 6 5 5 8 4 6 5 6 5 5 5 4 4 4 4 5 2 6 6
## [4609] 6 8 8 5 5 4 5 5 5 7 7 5 5 5 5 5 5 4 5 4 5 4 5 6
## [4633] 5 6 5 9 4 4 4 3 4 4 3 3 3 4 6 7 7 8 8 8 7 8 8 8
## [4657] 7 7 7 7 7 6 4 4 5 6 6 4 4 4 5 5 10 6 7 7 5 5 6 3
## [4681] 7 7 6 6 5 5 4 4 8 8 5 5 5 5 5 5 5 5 5 6 6 6 5 5
## [4705] 4 4 4 5 4 3 2 7 7 6 7 5 5 6 5 4 5 3 5 4 4 3 4 4
## [4729] 3 3 5 5 4 4 6 6 6 5 3 3 8 8 8 8 7 7 7 7 8 8 7 7
## [4753] 7 7 7 7 7 7 7 7 7 7 6 7 7 7 7 7 6 7 7 7 6 7 6 7
## [4777] 7 7 7 7 7 6 7 7 7 6 7 6 5 6 4 4 9 9 7 6 5 7 6 6
## [4801] 7 6 5 5 5 5 6 8 3 3 2 2 4 4 5 4 4 4 4 7 7 7 7 7
## [4825] 10 6 6 6 6 5 5 5 6 6 5 7 7 6 6 8 7 8 3 3 2 2 8 7
## [4849] 7 4 4 4 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5
## [4873] 5 5 5 5 4 5 5 5 5 5 5 7 6 6 6 5 6 5 5 4 6 6 6 5
## [4897] 6 5 4 4 5 5 5 5 4 5 4 4 4 4 3 4 5 5 3 4 4 4 5 5
## [4921] 5 6 3 3 2 2 2 2 3 3 3 7 6 9 6 6 6 6 8 8 10 10 7 6
## [4945] 6 7 6 8 7 8 7 8 7 7 5 7 5 5 6 4 7 6 8 10 10 10 10 10
## [4969] 10 10 10 4 4 4 6 9 7 6 9 9 8 8 8 8 8 8 5 5 5 7 7 3
## [4993] 10 10 10 9 6 6 6 6 3 2 2 5 4 5 4 5 4 4 4 4 4 3 3 3
## [5017] 3 3 5 5 5 5 8 8 6 8 7 7 6 8 6 8 7 6 8 6 6 5 10 6
## [5041] 8 7 7 8 6 8 7 7 8 7 7 7 8 7 6 7 7 6 8 10 5 8 7 7
## [5065] 8 5 5 4 5 5 5 7 7 5 5 7 5 5 5 7 7 5 5 5 5 7 6 5
## [5089] 5 7 7 5 5 5 5 5 7 7 6 6 7 2 3 2 3 2 3 2 3 3 2 6
## [5113] 7 6 6 6 6 6 7 5 6 5 5 5 3 5 5 5 6 4 6 5 4 5 4 5
## [5137] 5 5 4 4 6 6 6 4 2 3 2 3 2 6 6 6 6 6 7 7 6 8 8 8
## [5161] 6 6 6 6 6 5 6 5 6 5 6 6 6 6 6 6 6 5 5 5 5 5 5 5
## [5185] 5 6 6 7 7 5 5 5 5 4 4 5 5 5 5 5 5 4 4 4 4 4 4 5
## [5209] 4 4 6 4 10 10 5 5 5 5 5 5 5 5 4 4 4 4 4 4 4 3 3 3
## [5233] 3 3 3 3 3 6 5 7 5 5 5 5 5 3 5 6 4 3 3 5 4 3 6 6
## [5257] 4 4 5 3 4 7 7 6 7 5 5 5 5 5 5 5 6 5 10 6 5 6 5 6
## [5281] 5 4 4 6 5 5 4 6 5 5 5 3 10 10 3 3 4 4 5 4 4 3 3 4
## [5305] 5 6 5 4 5 6 5 5 6 5 5 4 5 3 4 5 8 8 7 6 7 7 7 8
## [5329] 8 5 4 6 4 0 0 5 6 4 6 7 10 6 4 4 4 4 3 3 4 3 3 3
## [5353] 7 7 7 8 7 7 7 8 7 7 7 7 8 8 10 3 3 4 4 4 4 3 4 7
## [5377] 6 7 7 5 5 5 4 5 5 5 4 4 5 4 4 4 3 3 4 3 3 4 4 5
## [5401] 5 5 5 3 4 7 6 6 7 6 8 8 8 6 6 5 3 5 3 4 4 5 4 4
## [5425] 2 4 4 4 7 6 8 7 6 7 6 7 6 7 5 10 10 9 4 5 4 5 5 6
## [5449] 5 6 6 6 4 3 3 3 4 4 4 5 4 4 5 4 4 3 4 7 7 8 7 4
## [5473] 3 4 10 7 7 8 7 8 5 6 6 10 7 6 6 9 6 5 4 6 5 4 5 4
## [5497] 3 4 4 4 5 5 5 6 5 5 5 6 5 5 5 0 3 4 5 5 6 5 5 4
## [5521] 5 3 0 0 4 4 4 4 3 3 4 3 3 3 5 4 6 4 4 3 4 3 4 3
## [5545] 4 3 7 6 7 6 5 6 8 8 7 8 8 7 7 6 8 8 8 8 8 7 7 7
## [5569] 7 7 5 5 5 5 5 7 7 5 5 8 7 7 7 6 6 7 4 4 4 4 5 4
## [5593] 4 5 5 5 5 5 5 4 4 8 6 7 9 9 6 7 6 5 6 7 6 6 7 7
## [5617] 7 7 6 5 5 5 7 7 5 5 5 5 4 5 4 4 7 4 4 5 5 6 6 4
## [5641] 4 3 2 5 4 5 4 4 4 4 5 5 5 4 5 4 5 5 4 5 4 4 5 4
## [5665] 5 5 5 5 5 6 6 5 5 5 5 5 5 5 5 6 6 5 5 3 2 5 5 5
## [5689] 5 5 6 6 6 6 5 6 4 4 4 4 5 7 7 7 5 7 5 6 7 6 6 4
## [5713] 4 8 6 7 6 7 9 8 7 7 7 4 5 4 5 5 4 5 5 5 5 6 6 6
## [5737] 6 10 5 5 5 5 3 3 5 3 3 4 5 5 3 4 3 4 6 6 9 9 5 6
## [5761] 5 5 5 5 7 4 3 6 5 5 5 4 4 4 4 4 2 6 5 5 8 8 6 5
## [5785] 5 5 4 5 5 7 7 5 5 5 4 4 4 3 4 4 5 4 4 4 5 6 4 6
## [5809] 5 9 4 3 3 3 4 4 4 3 2 3 4 4 8 8 7 7 8 8 8 7 8 7
## [5833] 8 7 7 7 7 7 6 6 5 7 7 4 4 4 4 4 4 6 4 4 4 4 2 6
## [5857] 2 2 2 4 4 4 2 2 4 3 5 10 7 6 5 7 6 5 5 5 4 8 7 5
## [5881] 5 5 5 5 5 5 5 5 4 5 5 4 2 7 6 5 5 5 4 4 6 4 4 2
## [5905] 5 5 4 4 4 3 5 4 7 5 7 7 7 7 6 7 7 8 7 8 6 7 6 6
## [5929] 7 6 7 7 6 6 7 6 7 6 7 7 6 6 6 6 6 6 7 6 10 7 6 7
## [5953] 6 6 6 6 5 6 6 6 6 5 5 5 5 4 6 7 7 4 4 5 4 3 4 4
## [5977] 7 7 7 6 6 10 10 6 5 5 7 7 6 5 5 5 5 5 7 7 8 7 8 8
## [6001] 7 7 5 5 5 5 5 5 5 5 5 4 5 5 5 5 5 5 5 5 5 4 5 5
## [6025] 5 5 3 3 3 5 5 5 5 5 5 4 4 4 4 6 5 6 5 5 5 4 5 4
## [6049] 4 3 3 6 5 4 6 5 5 5 4 4 5 5 5 4 4 5 4 4 4 4 3 3
## [6073] 4 2 3 4 5 5 2 2 2 2 2 2 2 2 3 3 7 6 8 8 8 7 6 6
## [6097] 8 8 10 10 7 6 6 6 6 7 7 7 7 7 7 7 5 7 5 5 5 4 7 6
## [6121] 7 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 4 4 4 5 9
## [6145] 7 6 9 9 8 8 7 7 8 8 5 5 4 7 7 2 10 10 10 9 6 6 8 6
## [6169] 6 2 2 2 5 4 5 5 4 4 4 4 2 3 2 2 3 2 8 8 6 7 7 6
## [6193] 6 7 6 6 6 6 6 4 10 6 7 7 6 6 7 7 7 7 6 7 8 7 8 6
## [6217] 9 5 7 5 5 4 5 5 6 5 7 6 5 7 5 7 5 5 6 5 7 5 4 5
## [6241] 5 6 5 5 6 5 5 5 7 4 5 4 5 5 5 5 6 5 6 4 6 6 3 2
## [6265] 7 6 5 6 6 5 6 6 7 6 6 5 5 5 5 5 5 5 4 4 5 3 3 3
## [6289] 5 4 4 4 4 4 3 4 6 6 5 2 4 2 3 2 3 2 6 6 5 6 6 6
## [6313] 6 6 8 8 8 6 5 6 6 6 5 5 5 5 5 6 6 5 6 6 6 6 5 5
## [6337] 5 5 5 5 5 5 5 4 3 5 5 5 5 5 5 4 4 4 3 4 3 5 5 4
## [6361] 4 3 3 10 10 5 4 5 5 5 5 5 5 4 4 4 4 4 4 2 3 2 3 2
## [6385] 3 2 6 5 5 5 4 4 5 2 4 5 4 3 2 4 4 3 5 3 3 6 7 6
## [6409] 6 5 5 5 5 5 5 5 5 5 5 5 6 5 5 5 4 4 5 4 4 5 5 3
## [6433] 5 5 3 3 3 5 4 5 4 3 3 3 10 2 5 5 4 4 5 4 2 5 5 5
## [6457] 4 5 4 5 4 2 4 2 4 3 8 7 7 7 8 7 5 3 5 4 0 0 5 5
## [6481] 7 6 10 4 3 3 3 3 3 3 3 6 7 6 7 6 7 6 7 8 8 8 7 2
## [6505] 3 4 3 4 3 3 3 6 6 6 6 5 5 4 5 5 4 4 5 5 10 5 4 3
## [6529] 3 3 4 2 3 2 3 5 4 3 5 4 4 2 3 4 3 3 4 4 4 4 4 4
## [6553] 3 3 3 7 6 8 7 7 7 6 7 5 5 6 5 10 10 9 5 4 4 5 4 5
## [6577] 5 5 6 5 5 3 3 3 2 4 4 4 3 4 5 4 4 4 4 4 4 4 4 4
## [6601] 3 2 2 4 5 3 4 4 4 3 4 2 7 7 8 7 3 3 4 10 7 7 7 6
## [6625] 8 5 5 5 4 10 6 5 5 9 5 4 3 5 4 3 5 3 5 3 5 5 3 2
## [6649] 4 4 4 5 4 4 5 5 5 5 5 5 0 4 5 3 4 3 4 4 5 4 5 4
## [6673] 3 3 5 5 4 5 4 5 4 2 0 0 4 3 3 3 3 3 3 3 5 3 5 4
## [6697] 4 3 4 3 3 3 3 2 7 5 7 5 4 6 10 8 8 7 8 8 8 7 8 8
## [6721] 8 7 8 6 7 6 7 8 8 7 7 7 7 7 6 5 5 4 5 5 4 5 7 7
## [6745] 5 5 8 7 7 7 5 6 6 8 10 10 10 4 4 5 5 5 5 4 5 4 4 7
## [6769] 7 6 9 9 5 6 5 5 6 6 6 6 7 7 6 7 5 6 5 5 7 6 5 5
## [6793] 5 5 5 5 5 4 4 4 3 4 7 6 5 4 4 5 5 6 6 3 4 2 2 4
## [6817] 7 5 4 5 4 3 3 4 4 5 3 5 3 5 5 8 5 8 5 8 5 8 3 4
## [6841] 4 3 4 4 5 5 5 4 5 5 5 5 5 4 4 5 5 5 5 5 5 4 4 3
## [6865] 2 5 4 5 5 5 5 5 5 5 6 5 6 3 3 3 3 5 6 7 6 6 6 5
## [6889] 6 6 6 3 4 10 10 9 7 5 6 7 9 7 7 7 4 4 4 5 5 4 4 5
## [6913] 5 4 6 6 6 6 10 5 4 5 6 5 5 3 3 2 2 5 2 4 5 5 5 2
## [6937] 2 4 5 9 9 5 6 5 5 5 5 7 4 2 6 4 5 4 4 3 4 3 2 5
## [6961] 5 5 7 6 4 5 4 4 5 5 7 4 4 4 4 4 4 4 5 3 4 3 4 4
## [6985] 4 4 5 4 5 4 9 3 3 3 2 4 4 4 4 4 2 2 2 2 3 3 3 8
## [7009] 8 7 6 7 7 7 7 7 7 7 6 7 7 5 5 7 7 4 4 5 5 5 4 4
## [7033] 4 4 4 4 6 3 4 5 4 4 4 4 2 2 2 3 3 3 3 3 2 4 2 5
## [7057] 10 6 6 5 5 6 6 7 6 4 4 5 5 5 5 5 4 4 6 6 5 5 5 4
## [7081] 4 4 4 2 4 2 5 5 4 4 4 4 2 2 2 5 4 6 6 6 5 6 7 7
## [7105] 6 7 7 7 7 6 5 6 5 6 6 6 6 6 6 6 5 6 5 6 6 10 7 6
## [7129] 6 9 8 8 8 6 6 5 6 5 6 5 4 4 4 6 7 7 2 2 4 4 4 4
## [7153] 3 3 3 3 3 7 7 6 6 6 10 5 5 5 5 5 5 4 5 6 7 8 8 7
## [7177] 7 7 6 6 6 3 3 3 8 7 7 5 5 5 5 5 5 5 4 5 4 5 5 5
## [7201] 5 5 5 5 4 5 4 5 5 5 5 5 5 5 4 5 5 4 4 4 4 5 5 5
## [7225] 5 4 4 4 4 3 3 5 4 4 4 4 3 4 2 3 4 5 2 3 2 8 8 8
## [7249] 8 6 5 7 6 5 6 5 7 6 7 6 7 6 7 5 5 7 5 6 4 5 4 10
## [7273] 10 10 10 10 10 10 10 10 6 5 3 3 3 5 9 5 6 9 9 7 7 7 7 7
## [7297] 8 8 5 5 5 5 6 7 5 2 10 10 10 10 9 5 5 7 6 5 2 5 4 4
## [7321] 4 4 4 4 3 3 2 2 2 2 2 2 7 8 8 8 6 6 6 6 6 5 4 7
## [7345] 7 5 6 5 5 7 6 5 6 6 6 6 7 7 8 6 5 6 5 4 4 6 6 5
## [7369] 7 6 7 5 5 6 6 6 5 7 5 5 5 5 6 5 5 5length(boxplot.stats(puntuacion_c)$out)## [1] 7386outliers <- boxplot.stats(puntuacion_c)$out
range(outliers)## [1] 0 10Tabla Indicadores estadisticos
cat("Tabla de Indicadores: Puntuación de Economía de Combustible\n")## Tabla de Indicadores: Puntuación de Economía de Combustibleprint(indicadores_puntuacion)## Indicador Valor
## 1 Moda 1.00
## 2 Mediana 1.00
## 3 Media (x̄) 1.61
## 4 Desviación Estándar (σ) 1.74
## 5 Varianza (σ²) 3.03
## 6 Coef. Variación (%) 108.21
## 7 Asimetría 2.54
## 8 Curtosis 5.81Conclusiones
El comportamiento de la variable puntuación de eocnomía fluctúa entre [0-10] y los valores se encuentran en torno a la mediana de 1, con una desviación estándar de 1.74, siendo un conjunto con un coeficiente de variación muy heterogéneo y tiene un sesgo positivo con existencia de valores atípicos a partir de la puntuación 2.