Practica4
Edgar Miguel Soto Trujillo 16040460
21/2/2020
#Mostrar datos y generar datos
set.seed(1000)
muestra <- sample(70:100, size = 1000, replace=TRUE)
muestra## [1] 85 73 80 91 88 93 98 72 98 87 91 75 82 75 70 78 98 95
## [19] 95 97 92 87 74 99 88 85 95 98 79 78 95 76 93 81 86 91
## [37] 93 97 96 77 88 72 96 75 76 82 91 75 76 85 97 77 72 90
## [55] 87 82 99 87 85 86 86 72 82 83 77 100 77 80 93 96 81 81
## [73] 95 79 80 93 95 85 84 81 75 78 91 90 80 90 100 80 79 79
## [91] 70 96 94 78 76 83 100 94 86 71 76 76 86 72 94 83 71 70
## [109] 88 90 75 77 89 100 73 78 91 92 83 94 85 97 74 88 94 95
## [127] 100 88 100 100 98 90 72 86 93 78 91 97 78 99 74 85 73 78
## [145] 75 97 81 94 80 88 79 77 100 84 79 93 88 98 88 87 77 86
## [163] 100 85 72 82 72 94 75 99 74 92 72 96 84 84 94 75 78 71
## [181] 89 87 98 77 98 70 80 93 86 74 74 97 99 85 100 84 99 78
## [199] 89 93 92 84 92 95 96 92 92 71 85 87 87 89 74 70 92 85
## [217] 75 94 97 86 93 77 93 88 93 100 76 91 96 77 100 89 94 98
## [235] 82 93 72 73 76 89 92 88 87 88 87 97 86 74 75 76 90 75
## [253] 97 89 78 89 73 89 72 79 74 80 72 92 70 82 70 82 91 97
## [271] 74 90 78 89 71 77 100 70 70 71 70 70 85 72 90 76 81 95
## [289] 84 93 78 77 95 88 76 71 95 88 96 84 90 77 88 84 91 77
## [307] 91 90 97 83 75 95 93 81 84 70 83 72 73 70 70 74 100 85
## [325] 94 98 94 91 73 100 73 84 87 87 85 77 89 99 84 95 95 100
## [343] 74 72 84 74 87 96 75 83 76 92 80 82 89 91 78 72 75 89
## [361] 86 83 82 88 91 90 89 82 97 75 84 81 83 98 74 74 78 78
## [379] 89 84 70 96 80 99 77 92 96 96 86 72 72 71 91 99 94 92
## [397] 76 93 81 74 100 95 93 94 79 98 98 98 99 94 86 81 99 89
## [415] 78 84 71 98 76 72 87 83 94 87 96 82 84 83 76 74 75 98
## [433] 77 84 84 91 94 81 98 85 73 85 100 75 96 80 73 74 90 93
## [451] 81 96 100 100 98 84 90 87 98 79 98 87 81 72 74 92 75 88
## [469] 91 92 76 83 74 97 70 96 81 99 81 81 91 71 75 96 88 96
## [487] 80 83 86 98 92 96 82 79 86 97 95 73 87 71 82 91 78 100
## [505] 84 85 98 88 71 70 96 88 83 85 81 77 75 79 90 96 73 80
## [523] 72 96 78 92 88 93 85 86 91 96 88 82 95 84 86 95 96 97
## [541] 82 72 78 87 74 73 75 91 96 93 100 74 80 95 70 100 90 85
## [559] 91 90 94 83 83 77 77 72 83 75 76 96 81 83 91 72 98 92
## [577] 78 73 83 97 70 87 73 89 80 72 96 80 75 89 96 88 89 81
## [595] 82 82 92 100 98 84 95 91 100 90 86 70 98 73 100 95 73 82
## [613] 91 72 70 86 83 87 95 80 95 91 93 79 74 78 94 87 71 73
## [631] 95 92 84 71 78 86 96 92 90 76 77 92 74 85 99 100 85 88
## [649] 83 75 76 79 90 87 97 95 99 89 82 91 70 87 90 96 95 97
## [667] 91 87 71 74 82 99 72 88 84 74 99 92 99 96 98 83 89 79
## [685] 79 86 83 90 83 70 81 82 95 88 93 81 78 84 99 74 83 72
## [703] 87 93 96 94 94 91 98 85 88 73 71 86 89 71 91 78 70 70
## [721] 83 98 99 92 70 91 77 99 75 78 73 99 90 91 71 92 77 78
## [739] 99 77 74 90 78 76 95 72 89 90 73 83 70 99 90 83 94 89
## [757] 79 82 82 95 95 97 74 86 95 85 79 74 82 96 73 76 79 85
## [775] 82 99 78 73 90 92 82 97 83 86 82 85 72 100 83 84 88 72
## [793] 91 86 76 93 98 85 98 97 75 78 100 81 75 93 79 93 81 94
## [811] 99 76 74 96 82 98 86 88 98 75 85 87 82 84 87 89 73 86
## [829] 85 75 75 95 71 99 95 98 92 88 71 82 96 96 90 91 78 77
## [847] 84 97 100 91 85 95 96 71 75 80 86 85 94 75 93 97 100 91
## [865] 84 99 79 92 82 90 100 74 87 98 85 92 74 96 97 99 89 100
## [883] 95 71 93 89 99 83 78 88 71 88 72 96 86 84 71 76 86 94
## [901] 91 96 94 75 71 95 74 98 93 71 95 73 92 84 81 75 98 89
## [919] 82 87 77 85 72 94 83 70 96 72 94 84 72 100 92 95 95 73
## [937] 77 72 79 90 72 80 85 92 90 92 93 92 97 92 83 87 95 97
## [955] 79 82 99 70 80 86 86 87 88 82 90 96 85 89 70 82 99 78
## [973] 85 100 96 86 81 91 74 84 70 100 95 75 86 72 95 99 97 85
## [991] 70 85 97 81 80 76 99 84 99 85#Ordenar datos y mostrar
muestraord <- sort(muestra)
muestraord## [1] 70 70 70 70 70 70 70 70 70 70 70 70 70 70 70 70 70 70
## [19] 70 70 70 70 70 70 70 70 70 70 70 70 70 70 71 71 71 71
## [37] 71 71 71 71 71 71 71 71 71 71 71 71 71 71 71 71 71 71
## [55] 71 71 71 71 72 72 72 72 72 72 72 72 72 72 72 72 72 72
## [73] 72 72 72 72 72 72 72 72 72 72 72 72 72 72 72 72 72 72
## [91] 72 72 72 72 72 72 73 73 73 73 73 73 73 73 73 73 73 73
## [109] 73 73 73 73 73 73 73 73 73 73 73 73 73 73 74 74 74 74
## [127] 74 74 74 74 74 74 74 74 74 74 74 74 74 74 74 74 74 74
## [145] 74 74 74 74 74 74 74 74 74 74 74 74 74 75 75 75 75 75
## [163] 75 75 75 75 75 75 75 75 75 75 75 75 75 75 75 75 75 75
## [181] 75 75 75 75 75 75 75 75 75 75 75 75 75 76 76 76 76 76
## [199] 76 76 76 76 76 76 76 76 76 76 76 76 76 76 76 76 76 76
## [217] 76 76 77 77 77 77 77 77 77 77 77 77 77 77 77 77 77 77
## [235] 77 77 77 77 77 77 77 77 77 77 77 78 78 78 78 78 78 78
## [253] 78 78 78 78 78 78 78 78 78 78 78 78 78 78 78 78 78 78
## [271] 78 78 78 78 78 78 78 78 79 79 79 79 79 79 79 79 79 79
## [289] 79 79 79 79 79 79 79 79 79 79 79 79 80 80 80 80 80 80
## [307] 80 80 80 80 80 80 80 80 80 80 80 80 80 80 80 81 81 81
## [325] 81 81 81 81 81 81 81 81 81 81 81 81 81 81 81 81 81 81
## [343] 81 81 81 81 81 82 82 82 82 82 82 82 82 82 82 82 82 82
## [361] 82 82 82 82 82 82 82 82 82 82 82 82 82 82 82 82 82 82
## [379] 82 82 82 82 82 83 83 83 83 83 83 83 83 83 83 83 83 83
## [397] 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83
## [415] 83 83 84 84 84 84 84 84 84 84 84 84 84 84 84 84 84 84
## [433] 84 84 84 84 84 84 84 84 84 84 84 84 84 84 84 84 84 84
## [451] 84 85 85 85 85 85 85 85 85 85 85 85 85 85 85 85 85 85
## [469] 85 85 85 85 85 85 85 85 85 85 85 85 85 85 85 85 85 85
## [487] 85 85 85 85 86 86 86 86 86 86 86 86 86 86 86 86 86 86
## [505] 86 86 86 86 86 86 86 86 86 86 86 86 86 86 86 86 86 86
## [523] 86 86 87 87 87 87 87 87 87 87 87 87 87 87 87 87 87 87
## [541] 87 87 87 87 87 87 87 87 87 87 87 87 87 87 87 87 88 88
## [559] 88 88 88 88 88 88 88 88 88 88 88 88 88 88 88 88 88 88
## [577] 88 88 88 88 88 88 88 88 88 88 88 88 88 89 89 89 89 89
## [595] 89 89 89 89 89 89 89 89 89 89 89 89 89 89 89 89 89 89
## [613] 89 89 89 89 89 89 90 90 90 90 90 90 90 90 90 90 90 90
## [631] 90 90 90 90 90 90 90 90 90 90 90 90 90 90 90 90 90 90
## [649] 90 91 91 91 91 91 91 91 91 91 91 91 91 91 91 91 91 91
## [667] 91 91 91 91 91 91 91 91 91 91 91 91 91 91 91 91 91 91
## [685] 91 91 91 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92
## [703] 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92
## [721] 92 92 93 93 93 93 93 93 93 93 93 93 93 93 93 93 93 93
## [739] 93 93 93 93 93 93 93 93 93 93 93 93 93 93 94 94 94 94
## [757] 94 94 94 94 94 94 94 94 94 94 94 94 94 94 94 94 94 94
## [775] 94 94 94 94 94 94 95 95 95 95 95 95 95 95 95 95 95 95
## [793] 95 95 95 95 95 95 95 95 95 95 95 95 95 95 95 95 95 95
## [811] 95 95 95 95 95 95 95 95 95 95 95 95 96 96 96 96 96 96
## [829] 96 96 96 96 96 96 96 96 96 96 96 96 96 96 96 96 96 96
## [847] 96 96 96 96 96 96 96 96 96 96 96 96 96 96 96 96 96 96
## [865] 96 97 97 97 97 97 97 97 97 97 97 97 97 97 97 97 97 97
## [883] 97 97 97 97 97 97 97 97 97 97 97 97 98 98 98 98 98 98
## [901] 98 98 98 98 98 98 98 98 98 98 98 98 98 98 98 98 98 98
## [919] 98 98 98 98 98 98 98 98 98 98 98 98 99 99 99 99 99 99
## [937] 99 99 99 99 99 99 99 99 99 99 99 99 99 99 99 99 99 99
## [955] 99 99 99 99 99 99 99 99 99 99 100 100 100 100 100 100 100 100
## [973] 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100
## [991] 100 100 100 100 100 100 100 100 100 100#Encontrar numero de elementos n, valores maximos y minimos, rango y amplitud del rango de la muestra
n <- length(muestra)
n## [1] 1000max(muestra)## [1] 100min(muestra)## [1] 70#RANGO
rango <- range(muestra) # Valores minimo a maximo
rango## [1] 70 100#AMPLITUD DEL RANGO
amplitud <- diff(rango)
amplitud## [1] 30#FORMA ABITUAL PARA AGRUPAR DATOS
#DETERMINAR INTERVALO DE 5
nointervalos <- 5 #numero de intervalos
rangointervalos <- amplitud / nointervalos
rangointervalos## [1] 6#PASTE SIGNIFICA CONCATENAR
print(paste("Los valores de cada grupo van ...","de", rangointervalos, "en", rangointervalos, "a partir de:", min (muestra)))## [1] "Los valores de cada grupo van ... de 6 en 6 a partir de: 70"#Mostrar tabla de frecuencia de datos agrupados
#Se empieza del valor menor para evitar errores de agrupamiento
tabla.intervalos <- transform(table(cut(muestra, breaks = 5)))
tabla.intervalos## Var1 Freq
## 1 (70,76] 218
## 2 (76,82] 165
## 3 (82,88] 206
## 4 (88,94] 191
## 5 (94,100] 220#Plot o graficar tabla de frecuencia
plot (tabla.intervalos, main = "¿De cual intervalo hay mas y menos elementos?")
#REGLA DE STURGES.
1 + 3.3222* (log10(n)) ##Redondeando hacia arriba entonces sale 6 igual que siguiente ## [1] 10.9666nointervalos <- nclass.Sturges(muestra)
nointervalos## [1] 11cut(muestra, breaks = nointervalos) #Cortes de cada intervalo ## [1] (83.6,86.4] (72.7,75.5] (78.2,80.9] (89.1,91.8] (86.4,89.1] (91.8,94.5]
## [7] (97.3,100] (70,72.7] (97.3,100] (86.4,89.1] (89.1,91.8] (72.7,75.5]
## [13] (80.9,83.6] (72.7,75.5] (70,72.7] (75.5,78.2] (97.3,100] (94.5,97.3]
## [19] (94.5,97.3] (94.5,97.3] (91.8,94.5] (86.4,89.1] (72.7,75.5] (97.3,100]
## [25] (86.4,89.1] (83.6,86.4] (94.5,97.3] (97.3,100] (78.2,80.9] (75.5,78.2]
## [31] (94.5,97.3] (75.5,78.2] (91.8,94.5] (80.9,83.6] (83.6,86.4] (89.1,91.8]
## [37] (91.8,94.5] (94.5,97.3] (94.5,97.3] (75.5,78.2] (86.4,89.1] (70,72.7]
## [43] (94.5,97.3] (72.7,75.5] (75.5,78.2] (80.9,83.6] (89.1,91.8] (72.7,75.5]
## [49] (75.5,78.2] (83.6,86.4] (94.5,97.3] (75.5,78.2] (70,72.7] (89.1,91.8]
## [55] (86.4,89.1] (80.9,83.6] (97.3,100] (86.4,89.1] (83.6,86.4] (83.6,86.4]
## [61] (83.6,86.4] (70,72.7] (80.9,83.6] (80.9,83.6] (75.5,78.2] (97.3,100]
## [67] (75.5,78.2] (78.2,80.9] (91.8,94.5] (94.5,97.3] (80.9,83.6] (80.9,83.6]
## [73] (94.5,97.3] (78.2,80.9] (78.2,80.9] (91.8,94.5] (94.5,97.3] (83.6,86.4]
## [79] (83.6,86.4] (80.9,83.6] (72.7,75.5] (75.5,78.2] (89.1,91.8] (89.1,91.8]
## [85] (78.2,80.9] (89.1,91.8] (97.3,100] (78.2,80.9] (78.2,80.9] (78.2,80.9]
## [91] (70,72.7] (94.5,97.3] (91.8,94.5] (75.5,78.2] (75.5,78.2] (80.9,83.6]
## [97] (97.3,100] (91.8,94.5] (83.6,86.4] (70,72.7] (75.5,78.2] (75.5,78.2]
## [103] (83.6,86.4] (70,72.7] (91.8,94.5] (80.9,83.6] (70,72.7] (70,72.7]
## [109] (86.4,89.1] (89.1,91.8] (72.7,75.5] (75.5,78.2] (86.4,89.1] (97.3,100]
## [115] (72.7,75.5] (75.5,78.2] (89.1,91.8] (91.8,94.5] (80.9,83.6] (91.8,94.5]
## [121] (83.6,86.4] (94.5,97.3] (72.7,75.5] (86.4,89.1] (91.8,94.5] (94.5,97.3]
## [127] (97.3,100] (86.4,89.1] (97.3,100] (97.3,100] (97.3,100] (89.1,91.8]
## [133] (70,72.7] (83.6,86.4] (91.8,94.5] (75.5,78.2] (89.1,91.8] (94.5,97.3]
## [139] (75.5,78.2] (97.3,100] (72.7,75.5] (83.6,86.4] (72.7,75.5] (75.5,78.2]
## [145] (72.7,75.5] (94.5,97.3] (80.9,83.6] (91.8,94.5] (78.2,80.9] (86.4,89.1]
## [151] (78.2,80.9] (75.5,78.2] (97.3,100] (83.6,86.4] (78.2,80.9] (91.8,94.5]
## [157] (86.4,89.1] (97.3,100] (86.4,89.1] (86.4,89.1] (75.5,78.2] (83.6,86.4]
## [163] (97.3,100] (83.6,86.4] (70,72.7] (80.9,83.6] (70,72.7] (91.8,94.5]
## [169] (72.7,75.5] (97.3,100] (72.7,75.5] (91.8,94.5] (70,72.7] (94.5,97.3]
## [175] (83.6,86.4] (83.6,86.4] (91.8,94.5] (72.7,75.5] (75.5,78.2] (70,72.7]
## [181] (86.4,89.1] (86.4,89.1] (97.3,100] (75.5,78.2] (97.3,100] (70,72.7]
## [187] (78.2,80.9] (91.8,94.5] (83.6,86.4] (72.7,75.5] (72.7,75.5] (94.5,97.3]
## [193] (97.3,100] (83.6,86.4] (97.3,100] (83.6,86.4] (97.3,100] (75.5,78.2]
## [199] (86.4,89.1] (91.8,94.5] (91.8,94.5] (83.6,86.4] (91.8,94.5] (94.5,97.3]
## [205] (94.5,97.3] (91.8,94.5] (91.8,94.5] (70,72.7] (83.6,86.4] (86.4,89.1]
## [211] (86.4,89.1] (86.4,89.1] (72.7,75.5] (70,72.7] (91.8,94.5] (83.6,86.4]
## [217] (72.7,75.5] (91.8,94.5] (94.5,97.3] (83.6,86.4] (91.8,94.5] (75.5,78.2]
## [223] (91.8,94.5] (86.4,89.1] (91.8,94.5] (97.3,100] (75.5,78.2] (89.1,91.8]
## [229] (94.5,97.3] (75.5,78.2] (97.3,100] (86.4,89.1] (91.8,94.5] (97.3,100]
## [235] (80.9,83.6] (91.8,94.5] (70,72.7] (72.7,75.5] (75.5,78.2] (86.4,89.1]
## [241] (91.8,94.5] (86.4,89.1] (86.4,89.1] (86.4,89.1] (86.4,89.1] (94.5,97.3]
## [247] (83.6,86.4] (72.7,75.5] (72.7,75.5] (75.5,78.2] (89.1,91.8] (72.7,75.5]
## [253] (94.5,97.3] (86.4,89.1] (75.5,78.2] (86.4,89.1] (72.7,75.5] (86.4,89.1]
## [259] (70,72.7] (78.2,80.9] (72.7,75.5] (78.2,80.9] (70,72.7] (91.8,94.5]
## [265] (70,72.7] (80.9,83.6] (70,72.7] (80.9,83.6] (89.1,91.8] (94.5,97.3]
## [271] (72.7,75.5] (89.1,91.8] (75.5,78.2] (86.4,89.1] (70,72.7] (75.5,78.2]
## [277] (97.3,100] (70,72.7] (70,72.7] (70,72.7] (70,72.7] (70,72.7]
## [283] (83.6,86.4] (70,72.7] (89.1,91.8] (75.5,78.2] (80.9,83.6] (94.5,97.3]
## [289] (83.6,86.4] (91.8,94.5] (75.5,78.2] (75.5,78.2] (94.5,97.3] (86.4,89.1]
## [295] (75.5,78.2] (70,72.7] (94.5,97.3] (86.4,89.1] (94.5,97.3] (83.6,86.4]
## [301] (89.1,91.8] (75.5,78.2] (86.4,89.1] (83.6,86.4] (89.1,91.8] (75.5,78.2]
## [307] (89.1,91.8] (89.1,91.8] (94.5,97.3] (80.9,83.6] (72.7,75.5] (94.5,97.3]
## [313] (91.8,94.5] (80.9,83.6] (83.6,86.4] (70,72.7] (80.9,83.6] (70,72.7]
## [319] (72.7,75.5] (70,72.7] (70,72.7] (72.7,75.5] (97.3,100] (83.6,86.4]
## [325] (91.8,94.5] (97.3,100] (91.8,94.5] (89.1,91.8] (72.7,75.5] (97.3,100]
## [331] (72.7,75.5] (83.6,86.4] (86.4,89.1] (86.4,89.1] (83.6,86.4] (75.5,78.2]
## [337] (86.4,89.1] (97.3,100] (83.6,86.4] (94.5,97.3] (94.5,97.3] (97.3,100]
## [343] (72.7,75.5] (70,72.7] (83.6,86.4] (72.7,75.5] (86.4,89.1] (94.5,97.3]
## [349] (72.7,75.5] (80.9,83.6] (75.5,78.2] (91.8,94.5] (78.2,80.9] (80.9,83.6]
## [355] (86.4,89.1] (89.1,91.8] (75.5,78.2] (70,72.7] (72.7,75.5] (86.4,89.1]
## [361] (83.6,86.4] (80.9,83.6] (80.9,83.6] (86.4,89.1] (89.1,91.8] (89.1,91.8]
## [367] (86.4,89.1] (80.9,83.6] (94.5,97.3] (72.7,75.5] (83.6,86.4] (80.9,83.6]
## [373] (80.9,83.6] (97.3,100] (72.7,75.5] (72.7,75.5] (75.5,78.2] (75.5,78.2]
## [379] (86.4,89.1] (83.6,86.4] (70,72.7] (94.5,97.3] (78.2,80.9] (97.3,100]
## [385] (75.5,78.2] (91.8,94.5] (94.5,97.3] (94.5,97.3] (83.6,86.4] (70,72.7]
## [391] (70,72.7] (70,72.7] (89.1,91.8] (97.3,100] (91.8,94.5] (91.8,94.5]
## [397] (75.5,78.2] (91.8,94.5] (80.9,83.6] (72.7,75.5] (97.3,100] (94.5,97.3]
## [403] (91.8,94.5] (91.8,94.5] (78.2,80.9] (97.3,100] (97.3,100] (97.3,100]
## [409] (97.3,100] (91.8,94.5] (83.6,86.4] (80.9,83.6] (97.3,100] (86.4,89.1]
## [415] (75.5,78.2] (83.6,86.4] (70,72.7] (97.3,100] (75.5,78.2] (70,72.7]
## [421] (86.4,89.1] (80.9,83.6] (91.8,94.5] (86.4,89.1] (94.5,97.3] (80.9,83.6]
## [427] (83.6,86.4] (80.9,83.6] (75.5,78.2] (72.7,75.5] (72.7,75.5] (97.3,100]
## [433] (75.5,78.2] (83.6,86.4] (83.6,86.4] (89.1,91.8] (91.8,94.5] (80.9,83.6]
## [439] (97.3,100] (83.6,86.4] (72.7,75.5] (83.6,86.4] (97.3,100] (72.7,75.5]
## [445] (94.5,97.3] (78.2,80.9] (72.7,75.5] (72.7,75.5] (89.1,91.8] (91.8,94.5]
## [451] (80.9,83.6] (94.5,97.3] (97.3,100] (97.3,100] (97.3,100] (83.6,86.4]
## [457] (89.1,91.8] (86.4,89.1] (97.3,100] (78.2,80.9] (97.3,100] (86.4,89.1]
## [463] (80.9,83.6] (70,72.7] (72.7,75.5] (91.8,94.5] (72.7,75.5] (86.4,89.1]
## [469] (89.1,91.8] (91.8,94.5] (75.5,78.2] (80.9,83.6] (72.7,75.5] (94.5,97.3]
## [475] (70,72.7] (94.5,97.3] (80.9,83.6] (97.3,100] (80.9,83.6] (80.9,83.6]
## [481] (89.1,91.8] (70,72.7] (72.7,75.5] (94.5,97.3] (86.4,89.1] (94.5,97.3]
## [487] (78.2,80.9] (80.9,83.6] (83.6,86.4] (97.3,100] (91.8,94.5] (94.5,97.3]
## [493] (80.9,83.6] (78.2,80.9] (83.6,86.4] (94.5,97.3] (94.5,97.3] (72.7,75.5]
## [499] (86.4,89.1] (70,72.7] (80.9,83.6] (89.1,91.8] (75.5,78.2] (97.3,100]
## [505] (83.6,86.4] (83.6,86.4] (97.3,100] (86.4,89.1] (70,72.7] (70,72.7]
## [511] (94.5,97.3] (86.4,89.1] (80.9,83.6] (83.6,86.4] (80.9,83.6] (75.5,78.2]
## [517] (72.7,75.5] (78.2,80.9] (89.1,91.8] (94.5,97.3] (72.7,75.5] (78.2,80.9]
## [523] (70,72.7] (94.5,97.3] (75.5,78.2] (91.8,94.5] (86.4,89.1] (91.8,94.5]
## [529] (83.6,86.4] (83.6,86.4] (89.1,91.8] (94.5,97.3] (86.4,89.1] (80.9,83.6]
## [535] (94.5,97.3] (83.6,86.4] (83.6,86.4] (94.5,97.3] (94.5,97.3] (94.5,97.3]
## [541] (80.9,83.6] (70,72.7] (75.5,78.2] (86.4,89.1] (72.7,75.5] (72.7,75.5]
## [547] (72.7,75.5] (89.1,91.8] (94.5,97.3] (91.8,94.5] (97.3,100] (72.7,75.5]
## [553] (78.2,80.9] (94.5,97.3] (70,72.7] (97.3,100] (89.1,91.8] (83.6,86.4]
## [559] (89.1,91.8] (89.1,91.8] (91.8,94.5] (80.9,83.6] (80.9,83.6] (75.5,78.2]
## [565] (75.5,78.2] (70,72.7] (80.9,83.6] (72.7,75.5] (75.5,78.2] (94.5,97.3]
## [571] (80.9,83.6] (80.9,83.6] (89.1,91.8] (70,72.7] (97.3,100] (91.8,94.5]
## [577] (75.5,78.2] (72.7,75.5] (80.9,83.6] (94.5,97.3] (70,72.7] (86.4,89.1]
## [583] (72.7,75.5] (86.4,89.1] (78.2,80.9] (70,72.7] (94.5,97.3] (78.2,80.9]
## [589] (72.7,75.5] (86.4,89.1] (94.5,97.3] (86.4,89.1] (86.4,89.1] (80.9,83.6]
## [595] (80.9,83.6] (80.9,83.6] (91.8,94.5] (97.3,100] (97.3,100] (83.6,86.4]
## [601] (94.5,97.3] (89.1,91.8] (97.3,100] (89.1,91.8] (83.6,86.4] (70,72.7]
## [607] (97.3,100] (72.7,75.5] (97.3,100] (94.5,97.3] (72.7,75.5] (80.9,83.6]
## [613] (89.1,91.8] (70,72.7] (70,72.7] (83.6,86.4] (80.9,83.6] (86.4,89.1]
## [619] (94.5,97.3] (78.2,80.9] (94.5,97.3] (89.1,91.8] (91.8,94.5] (78.2,80.9]
## [625] (72.7,75.5] (75.5,78.2] (91.8,94.5] (86.4,89.1] (70,72.7] (72.7,75.5]
## [631] (94.5,97.3] (91.8,94.5] (83.6,86.4] (70,72.7] (75.5,78.2] (83.6,86.4]
## [637] (94.5,97.3] (91.8,94.5] (89.1,91.8] (75.5,78.2] (75.5,78.2] (91.8,94.5]
## [643] (72.7,75.5] (83.6,86.4] (97.3,100] (97.3,100] (83.6,86.4] (86.4,89.1]
## [649] (80.9,83.6] (72.7,75.5] (75.5,78.2] (78.2,80.9] (89.1,91.8] (86.4,89.1]
## [655] (94.5,97.3] (94.5,97.3] (97.3,100] (86.4,89.1] (80.9,83.6] (89.1,91.8]
## [661] (70,72.7] (86.4,89.1] (89.1,91.8] (94.5,97.3] (94.5,97.3] (94.5,97.3]
## [667] (89.1,91.8] (86.4,89.1] (70,72.7] (72.7,75.5] (80.9,83.6] (97.3,100]
## [673] (70,72.7] (86.4,89.1] (83.6,86.4] (72.7,75.5] (97.3,100] (91.8,94.5]
## [679] (97.3,100] (94.5,97.3] (97.3,100] (80.9,83.6] (86.4,89.1] (78.2,80.9]
## [685] (78.2,80.9] (83.6,86.4] (80.9,83.6] (89.1,91.8] (80.9,83.6] (70,72.7]
## [691] (80.9,83.6] (80.9,83.6] (94.5,97.3] (86.4,89.1] (91.8,94.5] (80.9,83.6]
## [697] (75.5,78.2] (83.6,86.4] (97.3,100] (72.7,75.5] (80.9,83.6] (70,72.7]
## [703] (86.4,89.1] (91.8,94.5] (94.5,97.3] (91.8,94.5] (91.8,94.5] (89.1,91.8]
## [709] (97.3,100] (83.6,86.4] (86.4,89.1] (72.7,75.5] (70,72.7] (83.6,86.4]
## [715] (86.4,89.1] (70,72.7] (89.1,91.8] (75.5,78.2] (70,72.7] (70,72.7]
## [721] (80.9,83.6] (97.3,100] (97.3,100] (91.8,94.5] (70,72.7] (89.1,91.8]
## [727] (75.5,78.2] (97.3,100] (72.7,75.5] (75.5,78.2] (72.7,75.5] (97.3,100]
## [733] (89.1,91.8] (89.1,91.8] (70,72.7] (91.8,94.5] (75.5,78.2] (75.5,78.2]
## [739] (97.3,100] (75.5,78.2] (72.7,75.5] (89.1,91.8] (75.5,78.2] (75.5,78.2]
## [745] (94.5,97.3] (70,72.7] (86.4,89.1] (89.1,91.8] (72.7,75.5] (80.9,83.6]
## [751] (70,72.7] (97.3,100] (89.1,91.8] (80.9,83.6] (91.8,94.5] (86.4,89.1]
## [757] (78.2,80.9] (80.9,83.6] (80.9,83.6] (94.5,97.3] (94.5,97.3] (94.5,97.3]
## [763] (72.7,75.5] (83.6,86.4] (94.5,97.3] (83.6,86.4] (78.2,80.9] (72.7,75.5]
## [769] (80.9,83.6] (94.5,97.3] (72.7,75.5] (75.5,78.2] (78.2,80.9] (83.6,86.4]
## [775] (80.9,83.6] (97.3,100] (75.5,78.2] (72.7,75.5] (89.1,91.8] (91.8,94.5]
## [781] (80.9,83.6] (94.5,97.3] (80.9,83.6] (83.6,86.4] (80.9,83.6] (83.6,86.4]
## [787] (70,72.7] (97.3,100] (80.9,83.6] (83.6,86.4] (86.4,89.1] (70,72.7]
## [793] (89.1,91.8] (83.6,86.4] (75.5,78.2] (91.8,94.5] (97.3,100] (83.6,86.4]
## [799] (97.3,100] (94.5,97.3] (72.7,75.5] (75.5,78.2] (97.3,100] (80.9,83.6]
## [805] (72.7,75.5] (91.8,94.5] (78.2,80.9] (91.8,94.5] (80.9,83.6] (91.8,94.5]
## [811] (97.3,100] (75.5,78.2] (72.7,75.5] (94.5,97.3] (80.9,83.6] (97.3,100]
## [817] (83.6,86.4] (86.4,89.1] (97.3,100] (72.7,75.5] (83.6,86.4] (86.4,89.1]
## [823] (80.9,83.6] (83.6,86.4] (86.4,89.1] (86.4,89.1] (72.7,75.5] (83.6,86.4]
## [829] (83.6,86.4] (72.7,75.5] (72.7,75.5] (94.5,97.3] (70,72.7] (97.3,100]
## [835] (94.5,97.3] (97.3,100] (91.8,94.5] (86.4,89.1] (70,72.7] (80.9,83.6]
## [841] (94.5,97.3] (94.5,97.3] (89.1,91.8] (89.1,91.8] (75.5,78.2] (75.5,78.2]
## [847] (83.6,86.4] (94.5,97.3] (97.3,100] (89.1,91.8] (83.6,86.4] (94.5,97.3]
## [853] (94.5,97.3] (70,72.7] (72.7,75.5] (78.2,80.9] (83.6,86.4] (83.6,86.4]
## [859] (91.8,94.5] (72.7,75.5] (91.8,94.5] (94.5,97.3] (97.3,100] (89.1,91.8]
## [865] (83.6,86.4] (97.3,100] (78.2,80.9] (91.8,94.5] (80.9,83.6] (89.1,91.8]
## [871] (97.3,100] (72.7,75.5] (86.4,89.1] (97.3,100] (83.6,86.4] (91.8,94.5]
## [877] (72.7,75.5] (94.5,97.3] (94.5,97.3] (97.3,100] (86.4,89.1] (97.3,100]
## [883] (94.5,97.3] (70,72.7] (91.8,94.5] (86.4,89.1] (97.3,100] (80.9,83.6]
## [889] (75.5,78.2] (86.4,89.1] (70,72.7] (86.4,89.1] (70,72.7] (94.5,97.3]
## [895] (83.6,86.4] (83.6,86.4] (70,72.7] (75.5,78.2] (83.6,86.4] (91.8,94.5]
## [901] (89.1,91.8] (94.5,97.3] (91.8,94.5] (72.7,75.5] (70,72.7] (94.5,97.3]
## [907] (72.7,75.5] (97.3,100] (91.8,94.5] (70,72.7] (94.5,97.3] (72.7,75.5]
## [913] (91.8,94.5] (83.6,86.4] (80.9,83.6] (72.7,75.5] (97.3,100] (86.4,89.1]
## [919] (80.9,83.6] (86.4,89.1] (75.5,78.2] (83.6,86.4] (70,72.7] (91.8,94.5]
## [925] (80.9,83.6] (70,72.7] (94.5,97.3] (70,72.7] (91.8,94.5] (83.6,86.4]
## [931] (70,72.7] (97.3,100] (91.8,94.5] (94.5,97.3] (94.5,97.3] (72.7,75.5]
## [937] (75.5,78.2] (70,72.7] (78.2,80.9] (89.1,91.8] (70,72.7] (78.2,80.9]
## [943] (83.6,86.4] (91.8,94.5] (89.1,91.8] (91.8,94.5] (91.8,94.5] (91.8,94.5]
## [949] (94.5,97.3] (91.8,94.5] (80.9,83.6] (86.4,89.1] (94.5,97.3] (94.5,97.3]
## [955] (78.2,80.9] (80.9,83.6] (97.3,100] (70,72.7] (78.2,80.9] (83.6,86.4]
## [961] (83.6,86.4] (86.4,89.1] (86.4,89.1] (80.9,83.6] (89.1,91.8] (94.5,97.3]
## [967] (83.6,86.4] (86.4,89.1] (70,72.7] (80.9,83.6] (97.3,100] (75.5,78.2]
## [973] (83.6,86.4] (97.3,100] (94.5,97.3] (83.6,86.4] (80.9,83.6] (89.1,91.8]
## [979] (72.7,75.5] (83.6,86.4] (70,72.7] (97.3,100] (94.5,97.3] (72.7,75.5]
## [985] (83.6,86.4] (70,72.7] (94.5,97.3] (97.3,100] (94.5,97.3] (83.6,86.4]
## [991] (70,72.7] (83.6,86.4] (94.5,97.3] (80.9,83.6] (78.2,80.9] (75.5,78.2]
## [997] (97.3,100] (83.6,86.4] (97.3,100] (83.6,86.4]
## 11 Levels: (70,72.7] (72.7,75.5] (75.5,78.2] (78.2,80.9] ... (97.3,100]tabla.intervalos <- transform(table(cut(muestra, breaks = nointervalos))) # son 6
tabla.intervalos## Var1 Freq
## 1 (70,72.7] 96
## 2 (72.7,75.5] 97
## 3 (75.5,78.2] 85
## 4 (78.2,80.9] 43
## 5 (80.9,83.6] 95
## 6 (83.6,86.4] 108
## 7 (86.4,89.1] 94
## 8 (89.1,91.8] 69
## 9 (91.8,94.5] 93
## 10 (94.5,97.3] 114
## 11 (97.3,100] 106pie(tabla.intervalos$Freq, labels = paste(tabla.intervalos$Var1, "-", tabla.intervalos$Freq), main = "¿De cual intervalo hay mas y menos elementos?. Sturges")
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• Primer paso, para poder sacar el resultado debemos saber qué tipo de algoritmo utilizaremos, debemos saber si existe una correlación entre los datos en este caso a la hora de sacar esto nos da una correlación de 0.8357631 lo cual significa que existe una correlación positiva considerable lo cual nos dice que los datos son candidatos para aplicarles una regresión lineal
• Al momento de realizar el modelo le metemos nuevos datos los cuales son las distancia del viaje y nos arrojó los resultados de que es el costo de viaje
• Y final mente el costo del viaje es más alto entre más largo sea el viaje