——–

19041231 Osiris Ochoa Solis

19041239 Elias Jr. Ramos Lopez

19041216 Frida Krystel Herrera Hernández

19041198 Marco Daniel De La Torre Mendia

19041206 Irving alonso Galvan carabez

——–
Objetivo: Generar datos agrupados, tabla de frecuencia y gráfica de los datos agrupados
Proceso:
* Identificar y mostrar datos de la muestra
* Ordenar datos y mostrar
* Encontrar número de elementos n, valores mánimos y máximos , rango y amplitud del rango de la muestra
* Determianr número de intérvalos igual a 5
* Identificar rango de cada intérvalo mediante: VALOR MINIMO / INTERVALOS
* Mostrar tabla de frecuencia de datos agrupados
* Plot o graficar tabla de ffrecuencia

Identificar datos de la muestra

 datos <- sample(70:100, 1000, replace = TRUE)
 datos
##    [1]  88  80  75  86  83  98  80  71  81  78 100  75  83  75  94  80  98  88
##   [19]  90  75  97  96  92  86  70  86  87  92  72  83  98  86  71  94  99  86
##   [37]  94  86  78  78  76  88  94  81  70  80  72  87  78  77  85  89  92  94
##   [55]  92  95  82  85  79  83  81  97  87  75  92  83  96  75  88  91  88  71
##   [73]  83  76  75  78  70  80  94  98  84  93  77  90  88  99  76  82  91  86
##   [91]  75  85  73  81  83  80  89  84  99  97  98  71  98  90  80  95  83  79
##  [109]  70  75  80  70  85 100  93  72  95  93  91  75  86  71  98  99  74  98
##  [127]  98  82  74  86  92  71  70  79  86  82  77  96  70  94  73  75  72  75
##  [145]  95  78 100  91  87  81  80 100  75  72  85  89  76  71  72  80  77  81
##  [163]  73  95  87  81  90  98  70  83  91  95  89  81  91  84  90  75  98  72
##  [181]  78  72  75  96  79  82 100  93  76  91  94  80  93  72  92  90  82  75
##  [199]  93  73  80  87  71  71  95 100  97  92  86  83  84  79  86  77  71  95
##  [217]  91  81  97  89  82  73  85  92 100  91  93  75  84  90  71  99  72  93
##  [235]  99  93  82  82  91  92  91  88  77  96  90  85  71  86  94  94  74  70
##  [253]  85  82  72  88  77  74  88 100  75  88  86  95  82 100 100  73  81  89
##  [271]  95  81  98  70  90  74  80  88  78  85  81  90  81  74  88  74  83  75
##  [289]  71  98  73  86  82  99  74  87  85  87  84  90  91  80  82  78  71  79
##  [307]  91  95  98  90 100  98  83  91  78  89  99  74  81  79  99  84  83  86
##  [325]  70  91  96  87  88  95  77  95  95  89  77  74  83  78  89  78  90  79
##  [343]  77 100  98  98  87  91  94  85  78  89  86  74  84  78  91  92  79  82
##  [361]  94  81  87  83  94  73  73  84  75  93  90  80  97  74  95  97  97  89
##  [379]  78  91  92  79  73  74  80  77  70  72  74  84  90  80  75  70  72  71
##  [397]  97 100  80  91  89  79  87  72  93  75  92  71  84  70  75  77  86  70
##  [415]  94  93  90  70 100  93  97  76  94  75  92  98  80  94  72  85  97  74
##  [433]  88  88  92  77  93  85  96  97  98  72  75  92  86  71  94  77  76  82
##  [451]  94  86  71 100  93  71  84  88  84  81  81  83  88  77  89  94 100  92
##  [469]  85  81  77 100  88  80  72  92  94  81  78  94  79  97  88  77  74  88
##  [487]  75  80  89  80  82  81  97  85  79  91  88  72  73  86  77  84  79  75
##  [505]  84  98  72  71  98  76  93  85  80  79  95  79 100  76 100  76  76  86
##  [523]  86  74  99  70  89  71  81  96  90  89  84  81  73  71  87  76  70  71
##  [541]  91  70  76  74 100  72  85  74  81  79  96  70  85  70  84  86  70  70
##  [559]  82  97  73  95  91  92  83  77  82  80  79  91  98  98  87  74  93  74
##  [577]  71  82  80  78  72  90  79 100  99  93  92  72  91  92  75  90  76  91
##  [595]  74  90  83  74  84  75  98  73  99  90 100  74  86  83 100  78  96  99
##  [613]  98  79  71  84  88  91  96 100  89  72  70  99  99  94  86  72  84  90
##  [631]  88  89  83  72  91  94  90  93  86  70  86  94  90  90  85  74  86  79
##  [649]  98  70  72  91  70  97  81  79  88  95  71  76  85  99 100  88 100 100
##  [667]  71  85  91  73  88  71  91  71  95  94  84  85  72  87  79  81  90  87
##  [685]  83  70  79  93  97  78  83  95  90  84  72  88  83  95  73  71  78  86
##  [703]  95  88  93  93  78  85  83  90  85  84  85  91  92  76  75  88  85  92
##  [721]  99  72  99  77  86  79  81  74  93  81  87  97  96  85  96  71  95  70
##  [739] 100  86  77  78  78  97  96  99  98  86  71  76  94  79  82  74  78  99
##  [757]  90  97  96  95  77  72  86  84  96  86  81  78 100 100  90  75  88  70
##  [775]  78  97  98  92  74  79  88  99  94  80  77  71  73  79  76  94  97  82
##  [793]  87  75  99  94  85  82  70  75  97  89  70  72  77  89  85  88  89  73
##  [811]  97  83 100  91  79  82  74  87  78  87  78 100  86  80  75  73  70  87
##  [829]  80  93  94  99  76  75  72  72  86  92  91  77  92  88  72  87  88  75
##  [847]  99  85  80  97  76  74  91  88  96  78  93  84  72  71  74  91  94  94
##  [865]  89  93 100  72  79  95  70  77  79  75  93  85  87  88  81  86  70  71
##  [883]  95  96  87  87  78  93 100  80  70  75  74  97  85  86  72  92  77  97
##  [901]  91  80 100  79  71  94  92  97  71  85  98  96  80  79  84  93  82  93
##  [919]  94  80  96  94  80  85  98  84  96  88  96  71  70  70  79  89  71  96
##  [937]  97  83  93  94  79  79  86  77  99  85  71  95  78  76  70  76  78  97
##  [955]  88  93  96  89  91  80  98  84  77  77  76  72  77  95  78  98 100  97
##  [973]  98  90  90  80  93  78  78  86  73  77  95  86  78  89  71  92  81 100
##  [991]  87  78 100  79  98  91  80  84  71  92

Ordenar datos y mostrar

muestraord <- sort(datos)
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  70  70  70  70
##   [37]  70  70  70  71  71  71  71  71  71  71  71  71  71  71  71  71  71  71
##   [55]  71  71  71  71  71  71  71  71  71  71  71  71  71  71  71  71  71  71
##   [73]  71  71  71  71  71  71  71  71  71  72  72  72  72  72  72  72  72  72
##   [91]  72  72  72  72  72  72  72  72  72  72  72  72  72  72  72  72  72  72
##  [109]  72  72  72  72  72  72  72  72  72  72  72  73  73  73  73  73  73  73
##  [127]  73  73  73  73  73  73  73  73  73  73  73  73  73  74  74  74  74  74
##  [145]  74  74  74  74  74  74  74  74  74  74  74  74  74  74  74  74  74  74
##  [163]  74  74  74  74  74  74  74  74  74  75  75  75  75  75  75  75  75  75
##  [181]  75  75  75  75  75  75  75  75  75  75  75  75  75  75  75  75  75  75
##  [199]  75  75  75  75  75  75  75  75  75  75  75  76  76  76  76  76  76  76
##  [217]  76  76  76  76  76  76  76  76  76  76  76  76  76  76  76  76  77  77
##  [235]  77  77  77  77  77  77  77  77  77  77  77  77  77  77  77  77  77  77
##  [253]  77  77  77  77  77  77  77  77  77  77  77  77  78  78  78  78  78  78
##  [271]  78  78  78  78  78  78  78  78  78  78  78  78  78  78  78  78  78  78
##  [289]  78  78  78  78  78  78  78  78  78  78  78  78  78  79  79  79  79  79
##  [307]  79  79  79  79  79  79  79  79  79  79  79  79  79  79  79  79  79  79
##  [325]  79  79  79  79  79  79  79  79  79  79  79  79  79  79  80  80  80  80
##  [343]  80  80  80  80  80  80  80  80  80  80  80  80  80  80  80  80  80  80
##  [361]  80  80  80  80  80  80  80  80  80  80  80  80  80  80  80  81  81  81
##  [379]  81  81  81  81  81  81  81  81  81  81  81  81  81  81  81  81  81  81
##  [397]  81  81  81  81  81  81  81  81  81  82  82  82  82  82  82  82  82  82
##  [415]  82  82  82  82  82  82  82  82  82  82  82  82  82  82  82  83  83  83
##  [433]  83  83  83  83  83  83  83  83  83  83  83  83  83  83  83  83  83  83
##  [451]  83  83  83  83  83  84  84  84  84  84  84  84  84  84  84  84  84  84
##  [469]  84  84  84  84  84  84  84  84  84  84  84  84  84  84  84  84  85  85
##  [487]  85  85  85  85  85  85  85  85  85  85  85  85  85  85  85  85  85  85
##  [505]  85  85  85  85  85  85  85  85  85  85  85  85  85  85  85  86  86  86
##  [523]  86  86  86  86  86  86  86  86  86  86  86  86  86  86  86  86  86  86
##  [541]  86  86  86  86  86  86  86  86  86  86  86  86  86  86  86  86  86  86
##  [559]  86  86  86  87  87  87  87  87  87  87  87  87  87  87  87  87  87  87
##  [577]  87  87  87  87  87  87  87  87  87  87  87  88  88  88  88  88  88  88
##  [595]  88  88  88  88  88  88  88  88  88  88  88  88  88  88  88  88  88  88
##  [613]  88  88  88  88  88  88  88  88  88  88  88  88  88  89  89  89  89  89
##  [631]  89  89  89  89  89  89  89  89  89  89  89  89  89  89  89  89  89  89
##  [649]  89  89  90  90  90  90  90  90  90  90  90  90  90  90  90  90  90  90
##  [667]  90  90  90  90  90  90  90  90  90  90  90  90  90  90  90  90  91  91
##  [685]  91  91  91  91  91  91  91  91  91  91  91  91  91  91  91  91  91  91
##  [703]  91  91  91  91  91  91  91  91  91  91  91  91  91  91  91  91  91  91
##  [721]  92  92  92  92  92  92  92  92  92  92  92  92  92  92  92  92  92  92
##  [739]  92  92  92  92  92  92  92  92  92  92  92  92  93  93  93  93  93  93
##  [757]  93  93  93  93  93  93  93  93  93  93  93  93  93  93  93  93  93  93
##  [775]  93  93  93  93  93  93  93  93  93  94  94  94  94  94  94  94  94  94
##  [793]  94  94  94  94  94  94  94  94  94  94  94  94  94  94  94  94  94  94
##  [811]  94  94  94  94  94  94  94  94  94  95  95  95  95  95  95  95  95  95
##  [829]  95  95  95  95  95  95  95  95  95  95  95  95  95  95  95  95  95  95
##  [847]  95  95  96  96  96  96  96  96  96  96  96  96  96  96  96  96  96  96
##  [865]  96  96  96  96  96  96  96  96  97  97  97  97  97  97  97  97  97  97
##  [883]  97  97  97  97  97  97  97  97  97  97  97  97  97  97  97  97  97  97
##  [901]  97  97  97  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  98  98  98  98  98  98
##  [937]  98  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  99 100 100 100 100 100 100 100 100 100 100
##  [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 número de elementos n, valores máximos y míximos , rango y amplitud del rango de la muestra

n <- length(datos)
n
## [1] 1000
max(datos)
## [1] 100
min(datos)
## [1] 70
rango <- range(datos) 
rango
## [1]  70 100
amplitud <- max(datos) - min(datos)
amplitud
## [1] 30

FORMA HABITUAL PARA AGRUPAR DATOS

¿Cuántos intérvalos se quiere tener? ¿Cuántos grupos?]

* Determinar número de intervalos igual a 5

nointervalos <- 5
rangointervalos <- amplitud / nointervalos
rangointervalos
## [1] 6
print(paste("Los valores de cada grupos van ..."," de ", rangointervalos, " en  ", rangointervalos, " a partir de :", min(datos)))
## [1] "Los valores de cada grupos van ...  de  6  en   6  a partir de : 70"
tabla.intervalos <- transform(table(cut(datos, breaks = 5)))
tabla.intervalos
##       Var1 Freq
## 1  (70,76]  232
## 2  (76,82]  197
## 3  (82,88]  196
## 4  (88,94]  194
## 5 (94,100]  181
plot(tabla.intervalos, main = "¿De cuál intervalo hay más y menos elementos?")

REGLA DE STURGES.

¿De manera mantemática sugiere los intérvalos y las amplitudes de cada intervalo

¿Cuáles intérvalos genra? ¿cual es la amplitud de cada intérvalo?]

Fórmula: K=1+3.322(log N) /* Logaritmo de base 10 */

intervaloSugerido <-1 + 3.3222* (log10(n))
intervaloSugerido
## [1] 10.9666
nointervalos <- nclass.Sturges(datos)
nointervalos
## [1] 11
cut(datos, breaks = nointervalos)
##    [1] (86.4,89.1] (78.2,80.9] (72.7,75.5] (83.6,86.4] (80.9,83.6] (97.3,100] 
##    [7] (78.2,80.9] (70,72.7]   (80.9,83.6] (75.5,78.2] (97.3,100]  (72.7,75.5]
##   [13] (80.9,83.6] (72.7,75.5] (91.8,94.5] (78.2,80.9] (97.3,100]  (86.4,89.1]
##   [19] (89.1,91.8] (72.7,75.5] (94.5,97.3] (94.5,97.3] (91.8,94.5] (83.6,86.4]
##   [25] (70,72.7]   (83.6,86.4] (86.4,89.1] (91.8,94.5] (70,72.7]   (80.9,83.6]
##   [31] (97.3,100]  (83.6,86.4] (70,72.7]   (91.8,94.5] (97.3,100]  (83.6,86.4]
##   [37] (91.8,94.5] (83.6,86.4] (75.5,78.2] (75.5,78.2] (75.5,78.2] (86.4,89.1]
##   [43] (91.8,94.5] (80.9,83.6] (70,72.7]   (78.2,80.9] (70,72.7]   (86.4,89.1]
##   [49] (75.5,78.2] (75.5,78.2] (83.6,86.4] (86.4,89.1] (91.8,94.5] (91.8,94.5]
##   [55] (91.8,94.5] (94.5,97.3] (80.9,83.6] (83.6,86.4] (78.2,80.9] (80.9,83.6]
##   [61] (80.9,83.6] (94.5,97.3] (86.4,89.1] (72.7,75.5] (91.8,94.5] (80.9,83.6]
##   [67] (94.5,97.3] (72.7,75.5] (86.4,89.1] (89.1,91.8] (86.4,89.1] (70,72.7]  
##   [73] (80.9,83.6] (75.5,78.2] (72.7,75.5] (75.5,78.2] (70,72.7]   (78.2,80.9]
##   [79] (91.8,94.5] (97.3,100]  (83.6,86.4] (91.8,94.5] (75.5,78.2] (89.1,91.8]
##   [85] (86.4,89.1] (97.3,100]  (75.5,78.2] (80.9,83.6] (89.1,91.8] (83.6,86.4]
##   [91] (72.7,75.5] (83.6,86.4] (72.7,75.5] (80.9,83.6] (80.9,83.6] (78.2,80.9]
##   [97] (86.4,89.1] (83.6,86.4] (97.3,100]  (94.5,97.3] (97.3,100]  (70,72.7]  
##  [103] (97.3,100]  (89.1,91.8] (78.2,80.9] (94.5,97.3] (80.9,83.6] (78.2,80.9]
##  [109] (70,72.7]   (72.7,75.5] (78.2,80.9] (70,72.7]   (83.6,86.4] (97.3,100] 
##  [115] (91.8,94.5] (70,72.7]   (94.5,97.3] (91.8,94.5] (89.1,91.8] (72.7,75.5]
##  [121] (83.6,86.4] (70,72.7]   (97.3,100]  (97.3,100]  (72.7,75.5] (97.3,100] 
##  [127] (97.3,100]  (80.9,83.6] (72.7,75.5] (83.6,86.4] (91.8,94.5] (70,72.7]  
##  [133] (70,72.7]   (78.2,80.9] (83.6,86.4] (80.9,83.6] (75.5,78.2] (94.5,97.3]
##  [139] (70,72.7]   (91.8,94.5] (72.7,75.5] (72.7,75.5] (70,72.7]   (72.7,75.5]
##  [145] (94.5,97.3] (75.5,78.2] (97.3,100]  (89.1,91.8] (86.4,89.1] (80.9,83.6]
##  [151] (78.2,80.9] (97.3,100]  (72.7,75.5] (70,72.7]   (83.6,86.4] (86.4,89.1]
##  [157] (75.5,78.2] (70,72.7]   (70,72.7]   (78.2,80.9] (75.5,78.2] (80.9,83.6]
##  [163] (72.7,75.5] (94.5,97.3] (86.4,89.1] (80.9,83.6] (89.1,91.8] (97.3,100] 
##  [169] (70,72.7]   (80.9,83.6] (89.1,91.8] (94.5,97.3] (86.4,89.1] (80.9,83.6]
##  [175] (89.1,91.8] (83.6,86.4] (89.1,91.8] (72.7,75.5] (97.3,100]  (70,72.7]  
##  [181] (75.5,78.2] (70,72.7]   (72.7,75.5] (94.5,97.3] (78.2,80.9] (80.9,83.6]
##  [187] (97.3,100]  (91.8,94.5] (75.5,78.2] (89.1,91.8] (91.8,94.5] (78.2,80.9]
##  [193] (91.8,94.5] (70,72.7]   (91.8,94.5] (89.1,91.8] (80.9,83.6] (72.7,75.5]
##  [199] (91.8,94.5] (72.7,75.5] (78.2,80.9] (86.4,89.1] (70,72.7]   (70,72.7]  
##  [205] (94.5,97.3] (97.3,100]  (94.5,97.3] (91.8,94.5] (83.6,86.4] (80.9,83.6]
##  [211] (83.6,86.4] (78.2,80.9] (83.6,86.4] (75.5,78.2] (70,72.7]   (94.5,97.3]
##  [217] (89.1,91.8] (80.9,83.6] (94.5,97.3] (86.4,89.1] (80.9,83.6] (72.7,75.5]
##  [223] (83.6,86.4] (91.8,94.5] (97.3,100]  (89.1,91.8] (91.8,94.5] (72.7,75.5]
##  [229] (83.6,86.4] (89.1,91.8] (70,72.7]   (97.3,100]  (70,72.7]   (91.8,94.5]
##  [235] (97.3,100]  (91.8,94.5] (80.9,83.6] (80.9,83.6] (89.1,91.8] (91.8,94.5]
##  [241] (89.1,91.8] (86.4,89.1] (75.5,78.2] (94.5,97.3] (89.1,91.8] (83.6,86.4]
##  [247] (70,72.7]   (83.6,86.4] (91.8,94.5] (91.8,94.5] (72.7,75.5] (70,72.7]  
##  [253] (83.6,86.4] (80.9,83.6] (70,72.7]   (86.4,89.1] (75.5,78.2] (72.7,75.5]
##  [259] (86.4,89.1] (97.3,100]  (72.7,75.5] (86.4,89.1] (83.6,86.4] (94.5,97.3]
##  [265] (80.9,83.6] (97.3,100]  (97.3,100]  (72.7,75.5] (80.9,83.6] (86.4,89.1]
##  [271] (94.5,97.3] (80.9,83.6] (97.3,100]  (70,72.7]   (89.1,91.8] (72.7,75.5]
##  [277] (78.2,80.9] (86.4,89.1] (75.5,78.2] (83.6,86.4] (80.9,83.6] (89.1,91.8]
##  [283] (80.9,83.6] (72.7,75.5] (86.4,89.1] (72.7,75.5] (80.9,83.6] (72.7,75.5]
##  [289] (70,72.7]   (97.3,100]  (72.7,75.5] (83.6,86.4] (80.9,83.6] (97.3,100] 
##  [295] (72.7,75.5] (86.4,89.1] (83.6,86.4] (86.4,89.1] (83.6,86.4] (89.1,91.8]
##  [301] (89.1,91.8] (78.2,80.9] (80.9,83.6] (75.5,78.2] (70,72.7]   (78.2,80.9]
##  [307] (89.1,91.8] (94.5,97.3] (97.3,100]  (89.1,91.8] (97.3,100]  (97.3,100] 
##  [313] (80.9,83.6] (89.1,91.8] (75.5,78.2] (86.4,89.1] (97.3,100]  (72.7,75.5]
##  [319] (80.9,83.6] (78.2,80.9] (97.3,100]  (83.6,86.4] (80.9,83.6] (83.6,86.4]
##  [325] (70,72.7]   (89.1,91.8] (94.5,97.3] (86.4,89.1] (86.4,89.1] (94.5,97.3]
##  [331] (75.5,78.2] (94.5,97.3] (94.5,97.3] (86.4,89.1] (75.5,78.2] (72.7,75.5]
##  [337] (80.9,83.6] (75.5,78.2] (86.4,89.1] (75.5,78.2] (89.1,91.8] (78.2,80.9]
##  [343] (75.5,78.2] (97.3,100]  (97.3,100]  (97.3,100]  (86.4,89.1] (89.1,91.8]
##  [349] (91.8,94.5] (83.6,86.4] (75.5,78.2] (86.4,89.1] (83.6,86.4] (72.7,75.5]
##  [355] (83.6,86.4] (75.5,78.2] (89.1,91.8] (91.8,94.5] (78.2,80.9] (80.9,83.6]
##  [361] (91.8,94.5] (80.9,83.6] (86.4,89.1] (80.9,83.6] (91.8,94.5] (72.7,75.5]
##  [367] (72.7,75.5] (83.6,86.4] (72.7,75.5] (91.8,94.5] (89.1,91.8] (78.2,80.9]
##  [373] (94.5,97.3] (72.7,75.5] (94.5,97.3] (94.5,97.3] (94.5,97.3] (86.4,89.1]
##  [379] (75.5,78.2] (89.1,91.8] (91.8,94.5] (78.2,80.9] (72.7,75.5] (72.7,75.5]
##  [385] (78.2,80.9] (75.5,78.2] (70,72.7]   (70,72.7]   (72.7,75.5] (83.6,86.4]
##  [391] (89.1,91.8] (78.2,80.9] (72.7,75.5] (70,72.7]   (70,72.7]   (70,72.7]  
##  [397] (94.5,97.3] (97.3,100]  (78.2,80.9] (89.1,91.8] (86.4,89.1] (78.2,80.9]
##  [403] (86.4,89.1] (70,72.7]   (91.8,94.5] (72.7,75.5] (91.8,94.5] (70,72.7]  
##  [409] (83.6,86.4] (70,72.7]   (72.7,75.5] (75.5,78.2] (83.6,86.4] (70,72.7]  
##  [415] (91.8,94.5] (91.8,94.5] (89.1,91.8] (70,72.7]   (97.3,100]  (91.8,94.5]
##  [421] (94.5,97.3] (75.5,78.2] (91.8,94.5] (72.7,75.5] (91.8,94.5] (97.3,100] 
##  [427] (78.2,80.9] (91.8,94.5] (70,72.7]   (83.6,86.4] (94.5,97.3] (72.7,75.5]
##  [433] (86.4,89.1] (86.4,89.1] (91.8,94.5] (75.5,78.2] (91.8,94.5] (83.6,86.4]
##  [439] (94.5,97.3] (94.5,97.3] (97.3,100]  (70,72.7]   (72.7,75.5] (91.8,94.5]
##  [445] (83.6,86.4] (70,72.7]   (91.8,94.5] (75.5,78.2] (75.5,78.2] (80.9,83.6]
##  [451] (91.8,94.5] (83.6,86.4] (70,72.7]   (97.3,100]  (91.8,94.5] (70,72.7]  
##  [457] (83.6,86.4] (86.4,89.1] (83.6,86.4] (80.9,83.6] (80.9,83.6] (80.9,83.6]
##  [463] (86.4,89.1] (75.5,78.2] (86.4,89.1] (91.8,94.5] (97.3,100]  (91.8,94.5]
##  [469] (83.6,86.4] (80.9,83.6] (75.5,78.2] (97.3,100]  (86.4,89.1] (78.2,80.9]
##  [475] (70,72.7]   (91.8,94.5] (91.8,94.5] (80.9,83.6] (75.5,78.2] (91.8,94.5]
##  [481] (78.2,80.9] (94.5,97.3] (86.4,89.1] (75.5,78.2] (72.7,75.5] (86.4,89.1]
##  [487] (72.7,75.5] (78.2,80.9] (86.4,89.1] (78.2,80.9] (80.9,83.6] (80.9,83.6]
##  [493] (94.5,97.3] (83.6,86.4] (78.2,80.9] (89.1,91.8] (86.4,89.1] (70,72.7]  
##  [499] (72.7,75.5] (83.6,86.4] (75.5,78.2] (83.6,86.4] (78.2,80.9] (72.7,75.5]
##  [505] (83.6,86.4] (97.3,100]  (70,72.7]   (70,72.7]   (97.3,100]  (75.5,78.2]
##  [511] (91.8,94.5] (83.6,86.4] (78.2,80.9] (78.2,80.9] (94.5,97.3] (78.2,80.9]
##  [517] (97.3,100]  (75.5,78.2] (97.3,100]  (75.5,78.2] (75.5,78.2] (83.6,86.4]
##  [523] (83.6,86.4] (72.7,75.5] (97.3,100]  (70,72.7]   (86.4,89.1] (70,72.7]  
##  [529] (80.9,83.6] (94.5,97.3] (89.1,91.8] (86.4,89.1] (83.6,86.4] (80.9,83.6]
##  [535] (72.7,75.5] (70,72.7]   (86.4,89.1] (75.5,78.2] (70,72.7]   (70,72.7]  
##  [541] (89.1,91.8] (70,72.7]   (75.5,78.2] (72.7,75.5] (97.3,100]  (70,72.7]  
##  [547] (83.6,86.4] (72.7,75.5] (80.9,83.6] (78.2,80.9] (94.5,97.3] (70,72.7]  
##  [553] (83.6,86.4] (70,72.7]   (83.6,86.4] (83.6,86.4] (70,72.7]   (70,72.7]  
##  [559] (80.9,83.6] (94.5,97.3] (72.7,75.5] (94.5,97.3] (89.1,91.8] (91.8,94.5]
##  [565] (80.9,83.6] (75.5,78.2] (80.9,83.6] (78.2,80.9] (78.2,80.9] (89.1,91.8]
##  [571] (97.3,100]  (97.3,100]  (86.4,89.1] (72.7,75.5] (91.8,94.5] (72.7,75.5]
##  [577] (70,72.7]   (80.9,83.6] (78.2,80.9] (75.5,78.2] (70,72.7]   (89.1,91.8]
##  [583] (78.2,80.9] (97.3,100]  (97.3,100]  (91.8,94.5] (91.8,94.5] (70,72.7]  
##  [589] (89.1,91.8] (91.8,94.5] (72.7,75.5] (89.1,91.8] (75.5,78.2] (89.1,91.8]
##  [595] (72.7,75.5] (89.1,91.8] (80.9,83.6] (72.7,75.5] (83.6,86.4] (72.7,75.5]
##  [601] (97.3,100]  (72.7,75.5] (97.3,100]  (89.1,91.8] (97.3,100]  (72.7,75.5]
##  [607] (83.6,86.4] (80.9,83.6] (97.3,100]  (75.5,78.2] (94.5,97.3] (97.3,100] 
##  [613] (97.3,100]  (78.2,80.9] (70,72.7]   (83.6,86.4] (86.4,89.1] (89.1,91.8]
##  [619] (94.5,97.3] (97.3,100]  (86.4,89.1] (70,72.7]   (70,72.7]   (97.3,100] 
##  [625] (97.3,100]  (91.8,94.5] (83.6,86.4] (70,72.7]   (83.6,86.4] (89.1,91.8]
##  [631] (86.4,89.1] (86.4,89.1] (80.9,83.6] (70,72.7]   (89.1,91.8] (91.8,94.5]
##  [637] (89.1,91.8] (91.8,94.5] (83.6,86.4] (70,72.7]   (83.6,86.4] (91.8,94.5]
##  [643] (89.1,91.8] (89.1,91.8] (83.6,86.4] (72.7,75.5] (83.6,86.4] (78.2,80.9]
##  [649] (97.3,100]  (70,72.7]   (70,72.7]   (89.1,91.8] (70,72.7]   (94.5,97.3]
##  [655] (80.9,83.6] (78.2,80.9] (86.4,89.1] (94.5,97.3] (70,72.7]   (75.5,78.2]
##  [661] (83.6,86.4] (97.3,100]  (97.3,100]  (86.4,89.1] (97.3,100]  (97.3,100] 
##  [667] (70,72.7]   (83.6,86.4] (89.1,91.8] (72.7,75.5] (86.4,89.1] (70,72.7]  
##  [673] (89.1,91.8] (70,72.7]   (94.5,97.3] (91.8,94.5] (83.6,86.4] (83.6,86.4]
##  [679] (70,72.7]   (86.4,89.1] (78.2,80.9] (80.9,83.6] (89.1,91.8] (86.4,89.1]
##  [685] (80.9,83.6] (70,72.7]   (78.2,80.9] (91.8,94.5] (94.5,97.3] (75.5,78.2]
##  [691] (80.9,83.6] (94.5,97.3] (89.1,91.8] (83.6,86.4] (70,72.7]   (86.4,89.1]
##  [697] (80.9,83.6] (94.5,97.3] (72.7,75.5] (70,72.7]   (75.5,78.2] (83.6,86.4]
##  [703] (94.5,97.3] (86.4,89.1] (91.8,94.5] (91.8,94.5] (75.5,78.2] (83.6,86.4]
##  [709] (80.9,83.6] (89.1,91.8] (83.6,86.4] (83.6,86.4] (83.6,86.4] (89.1,91.8]
##  [715] (91.8,94.5] (75.5,78.2] (72.7,75.5] (86.4,89.1] (83.6,86.4] (91.8,94.5]
##  [721] (97.3,100]  (70,72.7]   (97.3,100]  (75.5,78.2] (83.6,86.4] (78.2,80.9]
##  [727] (80.9,83.6] (72.7,75.5] (91.8,94.5] (80.9,83.6] (86.4,89.1] (94.5,97.3]
##  [733] (94.5,97.3] (83.6,86.4] (94.5,97.3] (70,72.7]   (94.5,97.3] (70,72.7]  
##  [739] (97.3,100]  (83.6,86.4] (75.5,78.2] (75.5,78.2] (75.5,78.2] (94.5,97.3]
##  [745] (94.5,97.3] (97.3,100]  (97.3,100]  (83.6,86.4] (70,72.7]   (75.5,78.2]
##  [751] (91.8,94.5] (78.2,80.9] (80.9,83.6] (72.7,75.5] (75.5,78.2] (97.3,100] 
##  [757] (89.1,91.8] (94.5,97.3] (94.5,97.3] (94.5,97.3] (75.5,78.2] (70,72.7]  
##  [763] (83.6,86.4] (83.6,86.4] (94.5,97.3] (83.6,86.4] (80.9,83.6] (75.5,78.2]
##  [769] (97.3,100]  (97.3,100]  (89.1,91.8] (72.7,75.5] (86.4,89.1] (70,72.7]  
##  [775] (75.5,78.2] (94.5,97.3] (97.3,100]  (91.8,94.5] (72.7,75.5] (78.2,80.9]
##  [781] (86.4,89.1] (97.3,100]  (91.8,94.5] (78.2,80.9] (75.5,78.2] (70,72.7]  
##  [787] (72.7,75.5] (78.2,80.9] (75.5,78.2] (91.8,94.5] (94.5,97.3] (80.9,83.6]
##  [793] (86.4,89.1] (72.7,75.5] (97.3,100]  (91.8,94.5] (83.6,86.4] (80.9,83.6]
##  [799] (70,72.7]   (72.7,75.5] (94.5,97.3] (86.4,89.1] (70,72.7]   (70,72.7]  
##  [805] (75.5,78.2] (86.4,89.1] (83.6,86.4] (86.4,89.1] (86.4,89.1] (72.7,75.5]
##  [811] (94.5,97.3] (80.9,83.6] (97.3,100]  (89.1,91.8] (78.2,80.9] (80.9,83.6]
##  [817] (72.7,75.5] (86.4,89.1] (75.5,78.2] (86.4,89.1] (75.5,78.2] (97.3,100] 
##  [823] (83.6,86.4] (78.2,80.9] (72.7,75.5] (72.7,75.5] (70,72.7]   (86.4,89.1]
##  [829] (78.2,80.9] (91.8,94.5] (91.8,94.5] (97.3,100]  (75.5,78.2] (72.7,75.5]
##  [835] (70,72.7]   (70,72.7]   (83.6,86.4] (91.8,94.5] (89.1,91.8] (75.5,78.2]
##  [841] (91.8,94.5] (86.4,89.1] (70,72.7]   (86.4,89.1] (86.4,89.1] (72.7,75.5]
##  [847] (97.3,100]  (83.6,86.4] (78.2,80.9] (94.5,97.3] (75.5,78.2] (72.7,75.5]
##  [853] (89.1,91.8] (86.4,89.1] (94.5,97.3] (75.5,78.2] (91.8,94.5] (83.6,86.4]
##  [859] (70,72.7]   (70,72.7]   (72.7,75.5] (89.1,91.8] (91.8,94.5] (91.8,94.5]
##  [865] (86.4,89.1] (91.8,94.5] (97.3,100]  (70,72.7]   (78.2,80.9] (94.5,97.3]
##  [871] (70,72.7]   (75.5,78.2] (78.2,80.9] (72.7,75.5] (91.8,94.5] (83.6,86.4]
##  [877] (86.4,89.1] (86.4,89.1] (80.9,83.6] (83.6,86.4] (70,72.7]   (70,72.7]  
##  [883] (94.5,97.3] (94.5,97.3] (86.4,89.1] (86.4,89.1] (75.5,78.2] (91.8,94.5]
##  [889] (97.3,100]  (78.2,80.9] (70,72.7]   (72.7,75.5] (72.7,75.5] (94.5,97.3]
##  [895] (83.6,86.4] (83.6,86.4] (70,72.7]   (91.8,94.5] (75.5,78.2] (94.5,97.3]
##  [901] (89.1,91.8] (78.2,80.9] (97.3,100]  (78.2,80.9] (70,72.7]   (91.8,94.5]
##  [907] (91.8,94.5] (94.5,97.3] (70,72.7]   (83.6,86.4] (97.3,100]  (94.5,97.3]
##  [913] (78.2,80.9] (78.2,80.9] (83.6,86.4] (91.8,94.5] (80.9,83.6] (91.8,94.5]
##  [919] (91.8,94.5] (78.2,80.9] (94.5,97.3] (91.8,94.5] (78.2,80.9] (83.6,86.4]
##  [925] (97.3,100]  (83.6,86.4] (94.5,97.3] (86.4,89.1] (94.5,97.3] (70,72.7]  
##  [931] (70,72.7]   (70,72.7]   (78.2,80.9] (86.4,89.1] (70,72.7]   (94.5,97.3]
##  [937] (94.5,97.3] (80.9,83.6] (91.8,94.5] (91.8,94.5] (78.2,80.9] (78.2,80.9]
##  [943] (83.6,86.4] (75.5,78.2] (97.3,100]  (83.6,86.4] (70,72.7]   (94.5,97.3]
##  [949] (75.5,78.2] (75.5,78.2] (70,72.7]   (75.5,78.2] (75.5,78.2] (94.5,97.3]
##  [955] (86.4,89.1] (91.8,94.5] (94.5,97.3] (86.4,89.1] (89.1,91.8] (78.2,80.9]
##  [961] (97.3,100]  (83.6,86.4] (75.5,78.2] (75.5,78.2] (75.5,78.2] (70,72.7]  
##  [967] (75.5,78.2] (94.5,97.3] (75.5,78.2] (97.3,100]  (97.3,100]  (94.5,97.3]
##  [973] (97.3,100]  (89.1,91.8] (89.1,91.8] (78.2,80.9] (91.8,94.5] (75.5,78.2]
##  [979] (75.5,78.2] (83.6,86.4] (72.7,75.5] (75.5,78.2] (94.5,97.3] (83.6,86.4]
##  [985] (75.5,78.2] (86.4,89.1] (70,72.7]   (91.8,94.5] (80.9,83.6] (97.3,100] 
##  [991] (86.4,89.1] (75.5,78.2] (97.3,100]  (78.2,80.9] (97.3,100]  (89.1,91.8]
##  [997] (78.2,80.9] (83.6,86.4] (70,72.7]   (91.8,94.5]
## 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(datos, breaks = nointervalos)))
tabla.intervalos
##           Var1 Freq
## 1    (70,72.7]  119
## 2  (72.7,75.5]   90
## 3  (75.5,78.2]   92
## 4  (78.2,80.9]   74
## 5  (80.9,83.6]   80
## 6  (83.6,86.4]  106
## 7  (86.4,89.1]   89
## 8  (89.1,91.8]   70
## 9  (91.8,94.5]   99
## 10 (94.5,97.3]   84
## 11  (97.3,100]   97
pie(tabla.intervalos$Freq, labels = paste(tabla.intervalos$Var1, " - ", tabla.intervalos$Freq), main = "¿De cuál intervalo hay más y menos elementos?. Sturges")

——–

INTERPRETACION DE LOS DATOS

Como los datos fueron generados de manera aleatoria sin un motivo especifico no significan por si solos como tal pero el hecho de poder apreciarlos de esta manera nos permite visuzliar perfectamente un caso cuando tenemos muchos muestras.

Como nosoros tenemos muchas muestras y trabajar de manera individual con cada una de ellas seria algo muy tardo para los fines practicos que necesitamos, lo que hacemos es agrupar los datos por clases con un rango detrminado que nos permite juntar datos y manejarlos con el menor numero de variables posibles. Al dividir los datos por clases nosotros podemos hacerlo bajo nuestro propio criterio, pero lo mejor y lo mas optimo es dividir las secciones y determinar el numero de clases bajo la REGLA DE STURGES que nos permite determinar en base a N muestras cual seria el rango ideal para cada clases, dejandonos asi una forma de manejar los datos de manera comoda y sencilla, pudiendo trabajar con medidas de tendencia central sin tanta dispercion y facilitando el trabajo de interpretar los datos, ademas que permite una mejor interpretacion de los datos al tener menos variables en juego, pudiendo apreciar de manera mas sencilla los datos de manera grafica, ya que al manejarlos de manera desordenada sin una clases de por medio solo complicaria mas la utilizacion de la informacion. Es por la comodidad de esto que el dividir los datos por clases se ha vuelto algo muy recurrente, por ejemplo al agrupar a personas de cierto rango de edad para no poner todos las edades y mas cuando la variable edades no es lo mas importante, por lo que podemos inferir que el separar los datos por clases nos sirve para reducir y facilitar la informacion tanto al que maneja los datos como para el que los visualiza.

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