——–

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]  72  99  76  71  72  93  89  91  78  79  77  81  80  83  85  97  90  99
##   [19]  85  86  96  88  72  82  72  80  97  96  71  96  85  78  85  89  77  87
##   [37]  72  76 100  96  73  71  85  82  88  75  83  98  74  90  74  95  87  74
##   [55]  81  86  95  79  88  79  77  93  86  89  71  76  96  72  80  91  76  89
##   [73]  95  99  94  99  76  85  78  92  72  71  81  91  93  71  77  91  86  94
##   [91]  88  76  83  78  73  74  85  95  78  80  87  73  80  78  79  71  78  72
##  [109]  87  74  79  86  93  84  82 100  70  76 100  71  96  77  81  83  81  99
##  [127]  80  71  80  81  95  79  86  93  96  82  98  95  96  97  97  78  75  77
##  [145]  73  72  79  87  85  79  71  75  89  82  97  94  92  72  72  89  94  80
##  [163]  97  79  96  70  81  95  97  80  74  73  70  85 100  83  81  80  98  70
##  [181]  91  82 100  80  74  73  77  91  76  95  89  95  95  91  83  92  74  76
##  [199]  86  84  92  75  82  95  89  93  98  86  93  71  84  77  90  99  93  91
##  [217]  85  84  79  93  80  91 100  82  94  88  70  83  76  74  89  98  89  78
##  [235]  84  99  92  83  74  81  94  89  71  82  77  84  96  87  98  98  92  72
##  [253]  89  93  88  74  96  70  88  82  97  70  86  79  91  76  98  79  91  95
##  [271]  79  81 100  96  94  88  88  73  87  95 100  81  99  72  73  76  91  97
##  [289]  73  87  72  70  73  96  84 100  78  79  89  95  76  75  70  71  93  82
##  [307]  95  95  96  70  77  87  99  84  81  85  91  71  75  96  86  73  89  90
##  [325]  90  80  83  97  73  79  81  92  79  81  78  86  96  83  96  82 100  90
##  [343]  73  72  87  86  81  76  88  72  90  84  70  94  91  88  92  99  99  88
##  [361]  80  85  95  75  82  70  94  71  78  93  72  78  96  93  97  70  99  76
##  [379]  87  84  96  77 100  90  74  77  85  83 100  70  92  80  74  92  87  91
##  [397]  81  88  89  86  93  89  70  99  70 100  71  99  73  93  83  73  83  94
##  [415]  97  80  77  74  99  75  83  85  83  91  87  76  93  85  75  87  77  80
##  [433]  98  91  73 100  96  93  94  88  89  98 100 100  80  84  83  80  73  72
##  [451]  92  90  78  81  77  88  82  98  90  86  82  89  70  94  85  72  95  72
##  [469]  70  77  81  85  86  72  83  80  80  98  80  70  78  82  98 100  82  71
##  [487]  71  70  82  79  82  85  91 100  74  88  82  94  84  95  85  79  81  90
##  [505]  71 100  99  87  97  89  94  96  74  77  84  95  96  78  80  82  76  83
##  [523]  73  80  81  79  93  98  97  74  91  71  95  84  97  71  84  78  74  76
##  [541]  77  76  90  99  88  87  87  98  82  84  94  72  76  85  97  90  71  87
##  [559]  83  89  90  95  84  71  77  74  96  95  70  93  91  81  84  98  95  72
##  [577]  82  91  71  94  93  88  72  74  98  85  75  94  95  71  79  77  99  76
##  [595]  93  96  95  73  97  72  82 100 100  80  83  77  88  73  99  92  91  72
##  [613]  88  90  85  82 100  77  95  76  71  94  77  80  98  70  76  75  90  90
##  [631]  98  88  89  82  74  95  98  93  76  91  80  80  90  74  87  74  90  75
##  [649]  87  75  74  73  75  82  81  97  76  87 100  88  97  97  71 100  78  91
##  [667]  76  98  90  86  79  86  72  88  70  73  74  96  92  92  74  72  96  91
##  [685]  74 100  77  89  85  94  90  97  94  75  88  90  85  87  78  71  73  98
##  [703]  93  84  95  86  70  89  88  73  90  92  82  92  76  84  87  94  79  91
##  [721]  95  98  75  96  78  71  89  81  79  92 100  78  70  81  76  84  84  97
##  [739]  90  78  76  74  80  88  71  92  75  85  72  87  79  99  70  77  81  94
##  [757]  95  79  75  89  86  89  74  80  89  88  94  91  79  71  78  71  83  79
##  [775]  90  70  74  79  90  94  88  74  97  76  96  92  79  80  97 100  76  87
##  [793]  91  99  86  93  92 100  96  83  71  77  88  91  98  78  84  94  98  97
##  [811]  76  81  72  73  85  88  75  90  72  74  99  88  96  76  94  85  73  89
##  [829]  93  93  76  90  97  75  76  73  82  71  72  74  87  73  90  91  78  99
##  [847]  76 100  81  89  99  87  72  91  81  95  74  89 100  78  76  86  92 100
##  [865]  91  72  73  88  94  80  76  89  94  83  84  74  97  83  89  74  83  91
##  [883]  84  99  82  74  85  78  83  94  95  71  79  92  78  87  93  96  71  98
##  [901]  74  74  96  71  91  98  76  71  81  85  72  81  95  96  91  89 100  82
##  [919]  88  70  88  86  94  88  97 100  90  87  94  70  94  70  71  75  72  81
##  [937]  85  93  99 100  83  97  84  96  80  89  99  79  73  89  77  91  91  95
##  [955]  84  73  81  76  71  82  71 100  98 100  80  85  82  83  92  80  73  83
##  [973]  87  77  85 100  88  80  75  98  75  96  88  84  90  82  85  74  94  94
##  [991]  92  72  92  91  82  77  95  74  99  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  71  71  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  71  71  71  71  71  71  71  71  71  71  71  71  71  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  72  72  72  72  72  72  72  72  72  72  72  72
##  [109]  73  73  73  73  73  73  73  73  73  73  73  73  73  73  73  73  73  73
##  [127]  73  73  73  73  73  73  73  73  73  73  73  73  73  73  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  74  74  74  74  74  74  74  74  74
##  [181]  74  75  75  75  75  75  75  75  75  75  75  75  75  75  75  75  75  75
##  [199]  75  75  75  75  75  75  76  76  76  76  76  76  76  76  76  76  76  76
##  [217]  76  76  76  76  76  76  76  76  76  76  76  76  76  76  76  76  76  76
##  [235]  76  76  76  76  76  76  76  76  76  76  77  77  77  77  77  77  77  77
##  [253]  77  77  77  77  77  77  77  77  77  77  77  77  77  77  77  77  77  77
##  [271]  77  77  77  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  80  80  80  80  80  80  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  81  81  81  81  81  81  81  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  82  82  82  82  82  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  82  82  82
##  [433]  82  82  82  83  83  83  83  83  83  83  83  83  83  83  83  83  83  83
##  [451]  83  83  83  83  83  83  83  83  83  83  83  83  83  83  84  84  84  84
##  [469]  84  84  84  84  84  84  84  84  84  84  84  84  84  84  84  84  84  84
##  [487]  84  84  84  84  84  84  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  85  85  85
##  [523]  85  85  85  86  86  86  86  86  86  86  86  86  86  86  86  86  86  86
##  [541]  86  86  86  86  86  86  86  87  87  87  87  87  87  87  87  87  87  87
##  [559]  87  87  87  87  87  87  87  87  87  87  87  87  87  87  87  87  87  87
##  [577]  87  88  88  88  88  88  88  88  88  88  88  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  89  89  89  89  89  89  89  89  89  89  89  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  90  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  91  91  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  92  92
##  [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  93  93  93  93  93  93  93  93  93  93  93  93
##  [757]  93  93  93  93  93  93  93  93  93  93  93  93  93  93  93  93  94  94
##  [775]  94  94  94  94  94  94  94  94  94  94  94  94  94  94  94  94  94  94
##  [793]  94  94  94  94  94  94  94  94  94  94  94  94  94  94  95  95  95  95
##  [811]  95  95  95  95  95  95  95  95  95  95  95  95  95  95  95  95  95  95
##  [829]  95  95  95  95  95  95  95  95  95  95  95  95  95  95  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  96  96  96  96  96  96  96  96  96  96  96  96  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  97  97  97  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  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  99 100 100 100 100 100 100 100 100 100
##  [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]  244
## 2  (76,82]  191
## 3  (82,88]  179
## 4  (88,94]  192
## 5 (94,100]  194
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] (70,72.7]   (97.3,100]  (75.5,78.2] (70,72.7]   (70,72.7]   (91.8,94.5]
##    [7] (86.4,89.1] (89.1,91.8] (75.5,78.2] (78.2,80.9] (75.5,78.2] (80.9,83.6]
##   [13] (78.2,80.9] (80.9,83.6] (83.6,86.4] (94.5,97.3] (89.1,91.8] (97.3,100] 
##   [19] (83.6,86.4] (83.6,86.4] (94.5,97.3] (86.4,89.1] (70,72.7]   (80.9,83.6]
##   [25] (70,72.7]   (78.2,80.9] (94.5,97.3] (94.5,97.3] (70,72.7]   (94.5,97.3]
##   [31] (83.6,86.4] (75.5,78.2] (83.6,86.4] (86.4,89.1] (75.5,78.2] (86.4,89.1]
##   [37] (70,72.7]   (75.5,78.2] (97.3,100]  (94.5,97.3] (72.7,75.5] (70,72.7]  
##   [43] (83.6,86.4] (80.9,83.6] (86.4,89.1] (72.7,75.5] (80.9,83.6] (97.3,100] 
##   [49] (72.7,75.5] (89.1,91.8] (72.7,75.5] (94.5,97.3] (86.4,89.1] (72.7,75.5]
##   [55] (80.9,83.6] (83.6,86.4] (94.5,97.3] (78.2,80.9] (86.4,89.1] (78.2,80.9]
##   [61] (75.5,78.2] (91.8,94.5] (83.6,86.4] (86.4,89.1] (70,72.7]   (75.5,78.2]
##   [67] (94.5,97.3] (70,72.7]   (78.2,80.9] (89.1,91.8] (75.5,78.2] (86.4,89.1]
##   [73] (94.5,97.3] (97.3,100]  (91.8,94.5] (97.3,100]  (75.5,78.2] (83.6,86.4]
##   [79] (75.5,78.2] (91.8,94.5] (70,72.7]   (70,72.7]   (80.9,83.6] (89.1,91.8]
##   [85] (91.8,94.5] (70,72.7]   (75.5,78.2] (89.1,91.8] (83.6,86.4] (91.8,94.5]
##   [91] (86.4,89.1] (75.5,78.2] (80.9,83.6] (75.5,78.2] (72.7,75.5] (72.7,75.5]
##   [97] (83.6,86.4] (94.5,97.3] (75.5,78.2] (78.2,80.9] (86.4,89.1] (72.7,75.5]
##  [103] (78.2,80.9] (75.5,78.2] (78.2,80.9] (70,72.7]   (75.5,78.2] (70,72.7]  
##  [109] (86.4,89.1] (72.7,75.5] (78.2,80.9] (83.6,86.4] (91.8,94.5] (83.6,86.4]
##  [115] (80.9,83.6] (97.3,100]  (70,72.7]   (75.5,78.2] (97.3,100]  (70,72.7]  
##  [121] (94.5,97.3] (75.5,78.2] (80.9,83.6] (80.9,83.6] (80.9,83.6] (97.3,100] 
##  [127] (78.2,80.9] (70,72.7]   (78.2,80.9] (80.9,83.6] (94.5,97.3] (78.2,80.9]
##  [133] (83.6,86.4] (91.8,94.5] (94.5,97.3] (80.9,83.6] (97.3,100]  (94.5,97.3]
##  [139] (94.5,97.3] (94.5,97.3] (94.5,97.3] (75.5,78.2] (72.7,75.5] (75.5,78.2]
##  [145] (72.7,75.5] (70,72.7]   (78.2,80.9] (86.4,89.1] (83.6,86.4] (78.2,80.9]
##  [151] (70,72.7]   (72.7,75.5] (86.4,89.1] (80.9,83.6] (94.5,97.3] (91.8,94.5]
##  [157] (91.8,94.5] (70,72.7]   (70,72.7]   (86.4,89.1] (91.8,94.5] (78.2,80.9]
##  [163] (94.5,97.3] (78.2,80.9] (94.5,97.3] (70,72.7]   (80.9,83.6] (94.5,97.3]
##  [169] (94.5,97.3] (78.2,80.9] (72.7,75.5] (72.7,75.5] (70,72.7]   (83.6,86.4]
##  [175] (97.3,100]  (80.9,83.6] (80.9,83.6] (78.2,80.9] (97.3,100]  (70,72.7]  
##  [181] (89.1,91.8] (80.9,83.6] (97.3,100]  (78.2,80.9] (72.7,75.5] (72.7,75.5]
##  [187] (75.5,78.2] (89.1,91.8] (75.5,78.2] (94.5,97.3] (86.4,89.1] (94.5,97.3]
##  [193] (94.5,97.3] (89.1,91.8] (80.9,83.6] (91.8,94.5] (72.7,75.5] (75.5,78.2]
##  [199] (83.6,86.4] (83.6,86.4] (91.8,94.5] (72.7,75.5] (80.9,83.6] (94.5,97.3]
##  [205] (86.4,89.1] (91.8,94.5] (97.3,100]  (83.6,86.4] (91.8,94.5] (70,72.7]  
##  [211] (83.6,86.4] (75.5,78.2] (89.1,91.8] (97.3,100]  (91.8,94.5] (89.1,91.8]
##  [217] (83.6,86.4] (83.6,86.4] (78.2,80.9] (91.8,94.5] (78.2,80.9] (89.1,91.8]
##  [223] (97.3,100]  (80.9,83.6] (91.8,94.5] (86.4,89.1] (70,72.7]   (80.9,83.6]
##  [229] (75.5,78.2] (72.7,75.5] (86.4,89.1] (97.3,100]  (86.4,89.1] (75.5,78.2]
##  [235] (83.6,86.4] (97.3,100]  (91.8,94.5] (80.9,83.6] (72.7,75.5] (80.9,83.6]
##  [241] (91.8,94.5] (86.4,89.1] (70,72.7]   (80.9,83.6] (75.5,78.2] (83.6,86.4]
##  [247] (94.5,97.3] (86.4,89.1] (97.3,100]  (97.3,100]  (91.8,94.5] (70,72.7]  
##  [253] (86.4,89.1] (91.8,94.5] (86.4,89.1] (72.7,75.5] (94.5,97.3] (70,72.7]  
##  [259] (86.4,89.1] (80.9,83.6] (94.5,97.3] (70,72.7]   (83.6,86.4] (78.2,80.9]
##  [265] (89.1,91.8] (75.5,78.2] (97.3,100]  (78.2,80.9] (89.1,91.8] (94.5,97.3]
##  [271] (78.2,80.9] (80.9,83.6] (97.3,100]  (94.5,97.3] (91.8,94.5] (86.4,89.1]
##  [277] (86.4,89.1] (72.7,75.5] (86.4,89.1] (94.5,97.3] (97.3,100]  (80.9,83.6]
##  [283] (97.3,100]  (70,72.7]   (72.7,75.5] (75.5,78.2] (89.1,91.8] (94.5,97.3]
##  [289] (72.7,75.5] (86.4,89.1] (70,72.7]   (70,72.7]   (72.7,75.5] (94.5,97.3]
##  [295] (83.6,86.4] (97.3,100]  (75.5,78.2] (78.2,80.9] (86.4,89.1] (94.5,97.3]
##  [301] (75.5,78.2] (72.7,75.5] (70,72.7]   (70,72.7]   (91.8,94.5] (80.9,83.6]
##  [307] (94.5,97.3] (94.5,97.3] (94.5,97.3] (70,72.7]   (75.5,78.2] (86.4,89.1]
##  [313] (97.3,100]  (83.6,86.4] (80.9,83.6] (83.6,86.4] (89.1,91.8] (70,72.7]  
##  [319] (72.7,75.5] (94.5,97.3] (83.6,86.4] (72.7,75.5] (86.4,89.1] (89.1,91.8]
##  [325] (89.1,91.8] (78.2,80.9] (80.9,83.6] (94.5,97.3] (72.7,75.5] (78.2,80.9]
##  [331] (80.9,83.6] (91.8,94.5] (78.2,80.9] (80.9,83.6] (75.5,78.2] (83.6,86.4]
##  [337] (94.5,97.3] (80.9,83.6] (94.5,97.3] (80.9,83.6] (97.3,100]  (89.1,91.8]
##  [343] (72.7,75.5] (70,72.7]   (86.4,89.1] (83.6,86.4] (80.9,83.6] (75.5,78.2]
##  [349] (86.4,89.1] (70,72.7]   (89.1,91.8] (83.6,86.4] (70,72.7]   (91.8,94.5]
##  [355] (89.1,91.8] (86.4,89.1] (91.8,94.5] (97.3,100]  (97.3,100]  (86.4,89.1]
##  [361] (78.2,80.9] (83.6,86.4] (94.5,97.3] (72.7,75.5] (80.9,83.6] (70,72.7]  
##  [367] (91.8,94.5] (70,72.7]   (75.5,78.2] (91.8,94.5] (70,72.7]   (75.5,78.2]
##  [373] (94.5,97.3] (91.8,94.5] (94.5,97.3] (70,72.7]   (97.3,100]  (75.5,78.2]
##  [379] (86.4,89.1] (83.6,86.4] (94.5,97.3] (75.5,78.2] (97.3,100]  (89.1,91.8]
##  [385] (72.7,75.5] (75.5,78.2] (83.6,86.4] (80.9,83.6] (97.3,100]  (70,72.7]  
##  [391] (91.8,94.5] (78.2,80.9] (72.7,75.5] (91.8,94.5] (86.4,89.1] (89.1,91.8]
##  [397] (80.9,83.6] (86.4,89.1] (86.4,89.1] (83.6,86.4] (91.8,94.5] (86.4,89.1]
##  [403] (70,72.7]   (97.3,100]  (70,72.7]   (97.3,100]  (70,72.7]   (97.3,100] 
##  [409] (72.7,75.5] (91.8,94.5] (80.9,83.6] (72.7,75.5] (80.9,83.6] (91.8,94.5]
##  [415] (94.5,97.3] (78.2,80.9] (75.5,78.2] (72.7,75.5] (97.3,100]  (72.7,75.5]
##  [421] (80.9,83.6] (83.6,86.4] (80.9,83.6] (89.1,91.8] (86.4,89.1] (75.5,78.2]
##  [427] (91.8,94.5] (83.6,86.4] (72.7,75.5] (86.4,89.1] (75.5,78.2] (78.2,80.9]
##  [433] (97.3,100]  (89.1,91.8] (72.7,75.5] (97.3,100]  (94.5,97.3] (91.8,94.5]
##  [439] (91.8,94.5] (86.4,89.1] (86.4,89.1] (97.3,100]  (97.3,100]  (97.3,100] 
##  [445] (78.2,80.9] (83.6,86.4] (80.9,83.6] (78.2,80.9] (72.7,75.5] (70,72.7]  
##  [451] (91.8,94.5] (89.1,91.8] (75.5,78.2] (80.9,83.6] (75.5,78.2] (86.4,89.1]
##  [457] (80.9,83.6] (97.3,100]  (89.1,91.8] (83.6,86.4] (80.9,83.6] (86.4,89.1]
##  [463] (70,72.7]   (91.8,94.5] (83.6,86.4] (70,72.7]   (94.5,97.3] (70,72.7]  
##  [469] (70,72.7]   (75.5,78.2] (80.9,83.6] (83.6,86.4] (83.6,86.4] (70,72.7]  
##  [475] (80.9,83.6] (78.2,80.9] (78.2,80.9] (97.3,100]  (78.2,80.9] (70,72.7]  
##  [481] (75.5,78.2] (80.9,83.6] (97.3,100]  (97.3,100]  (80.9,83.6] (70,72.7]  
##  [487] (70,72.7]   (70,72.7]   (80.9,83.6] (78.2,80.9] (80.9,83.6] (83.6,86.4]
##  [493] (89.1,91.8] (97.3,100]  (72.7,75.5] (86.4,89.1] (80.9,83.6] (91.8,94.5]
##  [499] (83.6,86.4] (94.5,97.3] (83.6,86.4] (78.2,80.9] (80.9,83.6] (89.1,91.8]
##  [505] (70,72.7]   (97.3,100]  (97.3,100]  (86.4,89.1] (94.5,97.3] (86.4,89.1]
##  [511] (91.8,94.5] (94.5,97.3] (72.7,75.5] (75.5,78.2] (83.6,86.4] (94.5,97.3]
##  [517] (94.5,97.3] (75.5,78.2] (78.2,80.9] (80.9,83.6] (75.5,78.2] (80.9,83.6]
##  [523] (72.7,75.5] (78.2,80.9] (80.9,83.6] (78.2,80.9] (91.8,94.5] (97.3,100] 
##  [529] (94.5,97.3] (72.7,75.5] (89.1,91.8] (70,72.7]   (94.5,97.3] (83.6,86.4]
##  [535] (94.5,97.3] (70,72.7]   (83.6,86.4] (75.5,78.2] (72.7,75.5] (75.5,78.2]
##  [541] (75.5,78.2] (75.5,78.2] (89.1,91.8] (97.3,100]  (86.4,89.1] (86.4,89.1]
##  [547] (86.4,89.1] (97.3,100]  (80.9,83.6] (83.6,86.4] (91.8,94.5] (70,72.7]  
##  [553] (75.5,78.2] (83.6,86.4] (94.5,97.3] (89.1,91.8] (70,72.7]   (86.4,89.1]
##  [559] (80.9,83.6] (86.4,89.1] (89.1,91.8] (94.5,97.3] (83.6,86.4] (70,72.7]  
##  [565] (75.5,78.2] (72.7,75.5] (94.5,97.3] (94.5,97.3] (70,72.7]   (91.8,94.5]
##  [571] (89.1,91.8] (80.9,83.6] (83.6,86.4] (97.3,100]  (94.5,97.3] (70,72.7]  
##  [577] (80.9,83.6] (89.1,91.8] (70,72.7]   (91.8,94.5] (91.8,94.5] (86.4,89.1]
##  [583] (70,72.7]   (72.7,75.5] (97.3,100]  (83.6,86.4] (72.7,75.5] (91.8,94.5]
##  [589] (94.5,97.3] (70,72.7]   (78.2,80.9] (75.5,78.2] (97.3,100]  (75.5,78.2]
##  [595] (91.8,94.5] (94.5,97.3] (94.5,97.3] (72.7,75.5] (94.5,97.3] (70,72.7]  
##  [601] (80.9,83.6] (97.3,100]  (97.3,100]  (78.2,80.9] (80.9,83.6] (75.5,78.2]
##  [607] (86.4,89.1] (72.7,75.5] (97.3,100]  (91.8,94.5] (89.1,91.8] (70,72.7]  
##  [613] (86.4,89.1] (89.1,91.8] (83.6,86.4] (80.9,83.6] (97.3,100]  (75.5,78.2]
##  [619] (94.5,97.3] (75.5,78.2] (70,72.7]   (91.8,94.5] (75.5,78.2] (78.2,80.9]
##  [625] (97.3,100]  (70,72.7]   (75.5,78.2] (72.7,75.5] (89.1,91.8] (89.1,91.8]
##  [631] (97.3,100]  (86.4,89.1] (86.4,89.1] (80.9,83.6] (72.7,75.5] (94.5,97.3]
##  [637] (97.3,100]  (91.8,94.5] (75.5,78.2] (89.1,91.8] (78.2,80.9] (78.2,80.9]
##  [643] (89.1,91.8] (72.7,75.5] (86.4,89.1] (72.7,75.5] (89.1,91.8] (72.7,75.5]
##  [649] (86.4,89.1] (72.7,75.5] (72.7,75.5] (72.7,75.5] (72.7,75.5] (80.9,83.6]
##  [655] (80.9,83.6] (94.5,97.3] (75.5,78.2] (86.4,89.1] (97.3,100]  (86.4,89.1]
##  [661] (94.5,97.3] (94.5,97.3] (70,72.7]   (97.3,100]  (75.5,78.2] (89.1,91.8]
##  [667] (75.5,78.2] (97.3,100]  (89.1,91.8] (83.6,86.4] (78.2,80.9] (83.6,86.4]
##  [673] (70,72.7]   (86.4,89.1] (70,72.7]   (72.7,75.5] (72.7,75.5] (94.5,97.3]
##  [679] (91.8,94.5] (91.8,94.5] (72.7,75.5] (70,72.7]   (94.5,97.3] (89.1,91.8]
##  [685] (72.7,75.5] (97.3,100]  (75.5,78.2] (86.4,89.1] (83.6,86.4] (91.8,94.5]
##  [691] (89.1,91.8] (94.5,97.3] (91.8,94.5] (72.7,75.5] (86.4,89.1] (89.1,91.8]
##  [697] (83.6,86.4] (86.4,89.1] (75.5,78.2] (70,72.7]   (72.7,75.5] (97.3,100] 
##  [703] (91.8,94.5] (83.6,86.4] (94.5,97.3] (83.6,86.4] (70,72.7]   (86.4,89.1]
##  [709] (86.4,89.1] (72.7,75.5] (89.1,91.8] (91.8,94.5] (80.9,83.6] (91.8,94.5]
##  [715] (75.5,78.2] (83.6,86.4] (86.4,89.1] (91.8,94.5] (78.2,80.9] (89.1,91.8]
##  [721] (94.5,97.3] (97.3,100]  (72.7,75.5] (94.5,97.3] (75.5,78.2] (70,72.7]  
##  [727] (86.4,89.1] (80.9,83.6] (78.2,80.9] (91.8,94.5] (97.3,100]  (75.5,78.2]
##  [733] (70,72.7]   (80.9,83.6] (75.5,78.2] (83.6,86.4] (83.6,86.4] (94.5,97.3]
##  [739] (89.1,91.8] (75.5,78.2] (75.5,78.2] (72.7,75.5] (78.2,80.9] (86.4,89.1]
##  [745] (70,72.7]   (91.8,94.5] (72.7,75.5] (83.6,86.4] (70,72.7]   (86.4,89.1]
##  [751] (78.2,80.9] (97.3,100]  (70,72.7]   (75.5,78.2] (80.9,83.6] (91.8,94.5]
##  [757] (94.5,97.3] (78.2,80.9] (72.7,75.5] (86.4,89.1] (83.6,86.4] (86.4,89.1]
##  [763] (72.7,75.5] (78.2,80.9] (86.4,89.1] (86.4,89.1] (91.8,94.5] (89.1,91.8]
##  [769] (78.2,80.9] (70,72.7]   (75.5,78.2] (70,72.7]   (80.9,83.6] (78.2,80.9]
##  [775] (89.1,91.8] (70,72.7]   (72.7,75.5] (78.2,80.9] (89.1,91.8] (91.8,94.5]
##  [781] (86.4,89.1] (72.7,75.5] (94.5,97.3] (75.5,78.2] (94.5,97.3] (91.8,94.5]
##  [787] (78.2,80.9] (78.2,80.9] (94.5,97.3] (97.3,100]  (75.5,78.2] (86.4,89.1]
##  [793] (89.1,91.8] (97.3,100]  (83.6,86.4] (91.8,94.5] (91.8,94.5] (97.3,100] 
##  [799] (94.5,97.3] (80.9,83.6] (70,72.7]   (75.5,78.2] (86.4,89.1] (89.1,91.8]
##  [805] (97.3,100]  (75.5,78.2] (83.6,86.4] (91.8,94.5] (97.3,100]  (94.5,97.3]
##  [811] (75.5,78.2] (80.9,83.6] (70,72.7]   (72.7,75.5] (83.6,86.4] (86.4,89.1]
##  [817] (72.7,75.5] (89.1,91.8] (70,72.7]   (72.7,75.5] (97.3,100]  (86.4,89.1]
##  [823] (94.5,97.3] (75.5,78.2] (91.8,94.5] (83.6,86.4] (72.7,75.5] (86.4,89.1]
##  [829] (91.8,94.5] (91.8,94.5] (75.5,78.2] (89.1,91.8] (94.5,97.3] (72.7,75.5]
##  [835] (75.5,78.2] (72.7,75.5] (80.9,83.6] (70,72.7]   (70,72.7]   (72.7,75.5]
##  [841] (86.4,89.1] (72.7,75.5] (89.1,91.8] (89.1,91.8] (75.5,78.2] (97.3,100] 
##  [847] (75.5,78.2] (97.3,100]  (80.9,83.6] (86.4,89.1] (97.3,100]  (86.4,89.1]
##  [853] (70,72.7]   (89.1,91.8] (80.9,83.6] (94.5,97.3] (72.7,75.5] (86.4,89.1]
##  [859] (97.3,100]  (75.5,78.2] (75.5,78.2] (83.6,86.4] (91.8,94.5] (97.3,100] 
##  [865] (89.1,91.8] (70,72.7]   (72.7,75.5] (86.4,89.1] (91.8,94.5] (78.2,80.9]
##  [871] (75.5,78.2] (86.4,89.1] (91.8,94.5] (80.9,83.6] (83.6,86.4] (72.7,75.5]
##  [877] (94.5,97.3] (80.9,83.6] (86.4,89.1] (72.7,75.5] (80.9,83.6] (89.1,91.8]
##  [883] (83.6,86.4] (97.3,100]  (80.9,83.6] (72.7,75.5] (83.6,86.4] (75.5,78.2]
##  [889] (80.9,83.6] (91.8,94.5] (94.5,97.3] (70,72.7]   (78.2,80.9] (91.8,94.5]
##  [895] (75.5,78.2] (86.4,89.1] (91.8,94.5] (94.5,97.3] (70,72.7]   (97.3,100] 
##  [901] (72.7,75.5] (72.7,75.5] (94.5,97.3] (70,72.7]   (89.1,91.8] (97.3,100] 
##  [907] (75.5,78.2] (70,72.7]   (80.9,83.6] (83.6,86.4] (70,72.7]   (80.9,83.6]
##  [913] (94.5,97.3] (94.5,97.3] (89.1,91.8] (86.4,89.1] (97.3,100]  (80.9,83.6]
##  [919] (86.4,89.1] (70,72.7]   (86.4,89.1] (83.6,86.4] (91.8,94.5] (86.4,89.1]
##  [925] (94.5,97.3] (97.3,100]  (89.1,91.8] (86.4,89.1] (91.8,94.5] (70,72.7]  
##  [931] (91.8,94.5] (70,72.7]   (70,72.7]   (72.7,75.5] (70,72.7]   (80.9,83.6]
##  [937] (83.6,86.4] (91.8,94.5] (97.3,100]  (97.3,100]  (80.9,83.6] (94.5,97.3]
##  [943] (83.6,86.4] (94.5,97.3] (78.2,80.9] (86.4,89.1] (97.3,100]  (78.2,80.9]
##  [949] (72.7,75.5] (86.4,89.1] (75.5,78.2] (89.1,91.8] (89.1,91.8] (94.5,97.3]
##  [955] (83.6,86.4] (72.7,75.5] (80.9,83.6] (75.5,78.2] (70,72.7]   (80.9,83.6]
##  [961] (70,72.7]   (97.3,100]  (97.3,100]  (97.3,100]  (78.2,80.9] (83.6,86.4]
##  [967] (80.9,83.6] (80.9,83.6] (91.8,94.5] (78.2,80.9] (72.7,75.5] (80.9,83.6]
##  [973] (86.4,89.1] (75.5,78.2] (83.6,86.4] (97.3,100]  (86.4,89.1] (78.2,80.9]
##  [979] (72.7,75.5] (97.3,100]  (72.7,75.5] (94.5,97.3] (86.4,89.1] (83.6,86.4]
##  [985] (89.1,91.8] (80.9,83.6] (83.6,86.4] (72.7,75.5] (91.8,94.5] (91.8,94.5]
##  [991] (91.8,94.5] (70,72.7]   (91.8,94.5] (89.1,91.8] (80.9,83.6] (75.5,78.2]
##  [997] (94.5,97.3] (72.7,75.5] (97.3,100]  (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]  108
## 2  (72.7,75.5]   96
## 3  (75.5,78.2]   97
## 4  (78.2,80.9]   67
## 5  (80.9,83.6]   96
## 6  (83.6,86.4]   83
## 7  (86.4,89.1]  102
## 8  (89.1,91.8]   69
## 9  (91.8,94.5]   88
## 10 (94.5,97.3]  100
## 11  (97.3,100]   94
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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