——–

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

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  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  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  73  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  73  74  74  74
##  [127]  74  74  74  74  74  74  74  74  74  74  74  74  74  74  74  74  74  74
##  [145]  74  75  75  75  75  75  75  75  75  75  75  75  75  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  76  76  76  76  76  76  76  76  76  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  76  76  76  76  76  77  77  77  77  77  77  77  77  77  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  78  78  78  78  78  78  78  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  79  79  79  79  79  79  79  79  79  79  79  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  80  80  80  80  80  80  80  80  80  80  80  80  80  80  80  80  80
##  [343]  80  80  80  80  80  80  80  80  80  80  80  81  81  81  81  81  81  81
##  [361]  81  81  81  81  81  81  81  81  81  81  81  81  81  81  81  81  81  81
##  [379]  81  81  81  81  81  81  81  81  81  81  82  82  82  82  82  82  82  82
##  [397]  82  82  82  82  82  82  82  82  82  82  82  82  82  82  82  82  82  82
##  [415]  82  82  82  83  83  83  83  83  83  83  83  83  83  83  83  83  83  83
##  [433]  83  83  83  83  83  83  83  83  83  83  83  83  83  83  83  83  83  83
##  [451]  83  84  84  84  84  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  84  84
##  [487]  84  84  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  85  85  85
##  [523]  85  85  85  85  85  85  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  87  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  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  88  88  88  88  88  88  88  88  88  88  89  89  89  89  89  89
##  [631]  89  89  89  89  89  89  89  89  89  89  89  89  89  89  89  89  90  90
##  [649]  90  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  90  90  90  90
##  [685]  90  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  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  92  92  92  92  92  92  92  92  92  92  92  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  93  93  93  93  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  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  95  95  95  95
##  [847]  95  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  96  96  96  96  96
##  [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  97  97  97  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 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]  223
## 2  (76,82]  194
## 3  (82,88]  207
## 4  (88,94]  191
## 5 (94,100]  185
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] (89.1,91.8] (94.5,97.3] (78.2,80.9] (70,72.7]   (78.2,80.9] (86.4,89.1]
##    [7] (75.5,78.2] (72.7,75.5] (83.6,86.4] (86.4,89.1] (86.4,89.1] (91.8,94.5]
##   [13] (78.2,80.9] (97.3,100]  (70,72.7]   (91.8,94.5] (97.3,100]  (97.3,100] 
##   [19] (86.4,89.1] (78.2,80.9] (97.3,100]  (72.7,75.5] (83.6,86.4] (83.6,86.4]
##   [25] (97.3,100]  (89.1,91.8] (94.5,97.3] (94.5,97.3] (89.1,91.8] (70,72.7]  
##   [31] (75.5,78.2] (78.2,80.9] (97.3,100]  (91.8,94.5] (83.6,86.4] (72.7,75.5]
##   [37] (91.8,94.5] (89.1,91.8] (89.1,91.8] (80.9,83.6] (89.1,91.8] (75.5,78.2]
##   [43] (70,72.7]   (78.2,80.9] (86.4,89.1] (94.5,97.3] (83.6,86.4] (83.6,86.4]
##   [49] (91.8,94.5] (80.9,83.6] (94.5,97.3] (78.2,80.9] (97.3,100]  (97.3,100] 
##   [55] (97.3,100]  (89.1,91.8] (75.5,78.2] (91.8,94.5] (91.8,94.5] (91.8,94.5]
##   [61] (97.3,100]  (89.1,91.8] (80.9,83.6] (72.7,75.5] (94.5,97.3] (70,72.7]  
##   [67] (80.9,83.6] (94.5,97.3] (78.2,80.9] (80.9,83.6] (70,72.7]   (72.7,75.5]
##   [73] (89.1,91.8] (97.3,100]  (80.9,83.6] (72.7,75.5] (91.8,94.5] (86.4,89.1]
##   [79] (94.5,97.3] (91.8,94.5] (83.6,86.4] (91.8,94.5] (83.6,86.4] (80.9,83.6]
##   [85] (80.9,83.6] (91.8,94.5] (94.5,97.3] (91.8,94.5] (75.5,78.2] (80.9,83.6]
##   [91] (72.7,75.5] (78.2,80.9] (94.5,97.3] (72.7,75.5] (78.2,80.9] (94.5,97.3]
##   [97] (70,72.7]   (86.4,89.1] (72.7,75.5] (75.5,78.2] (97.3,100]  (72.7,75.5]
##  [103] (97.3,100]  (75.5,78.2] (78.2,80.9] (83.6,86.4] (72.7,75.5] (80.9,83.6]
##  [109] (86.4,89.1] (78.2,80.9] (91.8,94.5] (70,72.7]   (72.7,75.5] (94.5,97.3]
##  [115] (97.3,100]  (78.2,80.9] (97.3,100]  (91.8,94.5] (89.1,91.8] (97.3,100] 
##  [121] (78.2,80.9] (78.2,80.9] (94.5,97.3] (86.4,89.1] (97.3,100]  (80.9,83.6]
##  [127] (70,72.7]   (97.3,100]  (83.6,86.4] (83.6,86.4] (91.8,94.5] (86.4,89.1]
##  [133] (86.4,89.1] (75.5,78.2] (83.6,86.4] (94.5,97.3] (80.9,83.6] (86.4,89.1]
##  [139] (83.6,86.4] (94.5,97.3] (86.4,89.1] (97.3,100]  (80.9,83.6] (70,72.7]  
##  [145] (89.1,91.8] (94.5,97.3] (83.6,86.4] (78.2,80.9] (78.2,80.9] (70,72.7]  
##  [151] (91.8,94.5] (97.3,100]  (91.8,94.5] (89.1,91.8] (91.8,94.5] (70,72.7]  
##  [157] (91.8,94.5] (80.9,83.6] (89.1,91.8] (80.9,83.6] (97.3,100]  (86.4,89.1]
##  [163] (78.2,80.9] (89.1,91.8] (83.6,86.4] (80.9,83.6] (83.6,86.4] (75.5,78.2]
##  [169] (80.9,83.6] (72.7,75.5] (94.5,97.3] (83.6,86.4] (70,72.7]   (80.9,83.6]
##  [175] (80.9,83.6] (80.9,83.6] (78.2,80.9] (75.5,78.2] (75.5,78.2] (70,72.7]  
##  [181] (80.9,83.6] (78.2,80.9] (94.5,97.3] (86.4,89.1] (86.4,89.1] (97.3,100] 
##  [187] (94.5,97.3] (91.8,94.5] (75.5,78.2] (70,72.7]   (97.3,100]  (83.6,86.4]
##  [193] (89.1,91.8] (86.4,89.1] (78.2,80.9] (83.6,86.4] (97.3,100]  (83.6,86.4]
##  [199] (75.5,78.2] (94.5,97.3] (91.8,94.5] (97.3,100]  (89.1,91.8] (86.4,89.1]
##  [205] (75.5,78.2] (80.9,83.6] (83.6,86.4] (89.1,91.8] (70,72.7]   (70,72.7]  
##  [211] (97.3,100]  (78.2,80.9] (75.5,78.2] (70,72.7]   (75.5,78.2] (78.2,80.9]
##  [217] (83.6,86.4] (86.4,89.1] (75.5,78.2] (94.5,97.3] (83.6,86.4] (80.9,83.6]
##  [223] (70,72.7]   (86.4,89.1] (80.9,83.6] (91.8,94.5] (91.8,94.5] (86.4,89.1]
##  [229] (86.4,89.1] (94.5,97.3] (75.5,78.2] (80.9,83.6] (86.4,89.1] (83.6,86.4]
##  [235] (80.9,83.6] (75.5,78.2] (70,72.7]   (97.3,100]  (91.8,94.5] (91.8,94.5]
##  [241] (78.2,80.9] (89.1,91.8] (83.6,86.4] (83.6,86.4] (91.8,94.5] (97.3,100] 
##  [247] (91.8,94.5] (91.8,94.5] (70,72.7]   (80.9,83.6] (91.8,94.5] (89.1,91.8]
##  [253] (72.7,75.5] (70,72.7]   (75.5,78.2] (80.9,83.6] (89.1,91.8] (80.9,83.6]
##  [259] (75.5,78.2] (97.3,100]  (72.7,75.5] (80.9,83.6] (80.9,83.6] (97.3,100] 
##  [265] (83.6,86.4] (97.3,100]  (94.5,97.3] (75.5,78.2] (72.7,75.5] (80.9,83.6]
##  [271] (94.5,97.3] (97.3,100]  (94.5,97.3] (72.7,75.5] (72.7,75.5] (97.3,100] 
##  [277] (83.6,86.4] (70,72.7]   (83.6,86.4] (75.5,78.2] (97.3,100]  (75.5,78.2]
##  [283] (89.1,91.8] (75.5,78.2] (80.9,83.6] (75.5,78.2] (83.6,86.4] (94.5,97.3]
##  [289] (80.9,83.6] (83.6,86.4] (89.1,91.8] (89.1,91.8] (97.3,100]  (70,72.7]  
##  [295] (75.5,78.2] (89.1,91.8] (89.1,91.8] (78.2,80.9] (97.3,100]  (70,72.7]  
##  [301] (86.4,89.1] (97.3,100]  (78.2,80.9] (80.9,83.6] (72.7,75.5] (70,72.7]  
##  [307] (70,72.7]   (80.9,83.6] (86.4,89.1] (70,72.7]   (83.6,86.4] (75.5,78.2]
##  [313] (70,72.7]   (94.5,97.3] (91.8,94.5] (83.6,86.4] (80.9,83.6] (89.1,91.8]
##  [319] (75.5,78.2] (75.5,78.2] (91.8,94.5] (86.4,89.1] (80.9,83.6] (75.5,78.2]
##  [325] (83.6,86.4] (97.3,100]  (75.5,78.2] (72.7,75.5] (94.5,97.3] (91.8,94.5]
##  [331] (83.6,86.4] (70,72.7]   (75.5,78.2] (72.7,75.5] (80.9,83.6] (75.5,78.2]
##  [337] (78.2,80.9] (91.8,94.5] (86.4,89.1] (83.6,86.4] (70,72.7]   (72.7,75.5]
##  [343] (83.6,86.4] (83.6,86.4] (72.7,75.5] (80.9,83.6] (97.3,100]  (83.6,86.4]
##  [349] (94.5,97.3] (83.6,86.4] (70,72.7]   (89.1,91.8] (75.5,78.2] (72.7,75.5]
##  [355] (80.9,83.6] (75.5,78.2] (70,72.7]   (72.7,75.5] (75.5,78.2] (94.5,97.3]
##  [361] (72.7,75.5] (91.8,94.5] (83.6,86.4] (86.4,89.1] (83.6,86.4] (78.2,80.9]
##  [367] (86.4,89.1] (75.5,78.2] (75.5,78.2] (86.4,89.1] (91.8,94.5] (97.3,100] 
##  [373] (70,72.7]   (89.1,91.8] (94.5,97.3] (86.4,89.1] (83.6,86.4] (75.5,78.2]
##  [379] (72.7,75.5] (91.8,94.5] (97.3,100]  (80.9,83.6] (91.8,94.5] (80.9,83.6]
##  [385] (75.5,78.2] (70,72.7]   (83.6,86.4] (83.6,86.4] (91.8,94.5] (97.3,100] 
##  [391] (91.8,94.5] (83.6,86.4] (75.5,78.2] (97.3,100]  (91.8,94.5] (75.5,78.2]
##  [397] (97.3,100]  (83.6,86.4] (94.5,97.3] (78.2,80.9] (97.3,100]  (70,72.7]  
##  [403] (75.5,78.2] (91.8,94.5] (80.9,83.6] (94.5,97.3] (89.1,91.8] (97.3,100] 
##  [409] (89.1,91.8] (91.8,94.5] (75.5,78.2] (83.6,86.4] (94.5,97.3] (72.7,75.5]
##  [415] (83.6,86.4] (78.2,80.9] (75.5,78.2] (75.5,78.2] (97.3,100]  (70,72.7]  
##  [421] (83.6,86.4] (75.5,78.2] (83.6,86.4] (75.5,78.2] (86.4,89.1] (97.3,100] 
##  [427] (75.5,78.2] (83.6,86.4] (70,72.7]   (91.8,94.5] (78.2,80.9] (97.3,100] 
##  [433] (72.7,75.5] (75.5,78.2] (86.4,89.1] (80.9,83.6] (91.8,94.5] (94.5,97.3]
##  [439] (86.4,89.1] (94.5,97.3] (86.4,89.1] (91.8,94.5] (89.1,91.8] (89.1,91.8]
##  [445] (89.1,91.8] (72.7,75.5] (91.8,94.5] (83.6,86.4] (75.5,78.2] (97.3,100] 
##  [451] (83.6,86.4] (97.3,100]  (86.4,89.1] (78.2,80.9] (72.7,75.5] (70,72.7]  
##  [457] (72.7,75.5] (75.5,78.2] (91.8,94.5] (70,72.7]   (72.7,75.5] (80.9,83.6]
##  [463] (89.1,91.8] (72.7,75.5] (80.9,83.6] (80.9,83.6] (78.2,80.9] (75.5,78.2]
##  [469] (80.9,83.6] (83.6,86.4] (86.4,89.1] (80.9,83.6] (86.4,89.1] (78.2,80.9]
##  [475] (91.8,94.5] (83.6,86.4] (83.6,86.4] (78.2,80.9] (94.5,97.3] (83.6,86.4]
##  [481] (78.2,80.9] (80.9,83.6] (94.5,97.3] (70,72.7]   (80.9,83.6] (91.8,94.5]
##  [487] (83.6,86.4] (80.9,83.6] (91.8,94.5] (97.3,100]  (70,72.7]   (86.4,89.1]
##  [493] (94.5,97.3] (72.7,75.5] (75.5,78.2] (86.4,89.1] (89.1,91.8] (70,72.7]  
##  [499] (83.6,86.4] (94.5,97.3] (83.6,86.4] (83.6,86.4] (75.5,78.2] (72.7,75.5]
##  [505] (70,72.7]   (91.8,94.5] (86.4,89.1] (72.7,75.5] (72.7,75.5] (86.4,89.1]
##  [511] (97.3,100]  (72.7,75.5] (86.4,89.1] (70,72.7]   (89.1,91.8] (72.7,75.5]
##  [517] (75.5,78.2] (70,72.7]   (86.4,89.1] (83.6,86.4] (80.9,83.6] (94.5,97.3]
##  [523] (91.8,94.5] (91.8,94.5] (86.4,89.1] (86.4,89.1] (83.6,86.4] (78.2,80.9]
##  [529] (75.5,78.2] (89.1,91.8] (75.5,78.2] (86.4,89.1] (80.9,83.6] (86.4,89.1]
##  [535] (91.8,94.5] (72.7,75.5] (83.6,86.4] (83.6,86.4] (83.6,86.4] (86.4,89.1]
##  [541] (78.2,80.9] (94.5,97.3] (97.3,100]  (75.5,78.2] (75.5,78.2] (86.4,89.1]
##  [547] (86.4,89.1] (94.5,97.3] (75.5,78.2] (75.5,78.2] (70,72.7]   (80.9,83.6]
##  [553] (94.5,97.3] (70,72.7]   (89.1,91.8] (70,72.7]   (72.7,75.5] (94.5,97.3]
##  [559] (72.7,75.5] (97.3,100]  (94.5,97.3] (72.7,75.5] (83.6,86.4] (72.7,75.5]
##  [565] (97.3,100]  (70,72.7]   (83.6,86.4] (89.1,91.8] (80.9,83.6] (89.1,91.8]
##  [571] (97.3,100]  (72.7,75.5] (75.5,78.2] (80.9,83.6] (83.6,86.4] (83.6,86.4]
##  [577] (80.9,83.6] (83.6,86.4] (89.1,91.8] (80.9,83.6] (97.3,100]  (97.3,100] 
##  [583] (80.9,83.6] (86.4,89.1] (97.3,100]  (78.2,80.9] (70,72.7]   (78.2,80.9]
##  [589] (80.9,83.6] (83.6,86.4] (94.5,97.3] (91.8,94.5] (91.8,94.5] (70,72.7]  
##  [595] (97.3,100]  (83.6,86.4] (70,72.7]   (89.1,91.8] (89.1,91.8] (89.1,91.8]
##  [601] (97.3,100]  (70,72.7]   (83.6,86.4] (70,72.7]   (75.5,78.2] (94.5,97.3]
##  [607] (86.4,89.1] (78.2,80.9] (72.7,75.5] (75.5,78.2] (72.7,75.5] (75.5,78.2]
##  [613] (80.9,83.6] (75.5,78.2] (94.5,97.3] (70,72.7]   (94.5,97.3] (91.8,94.5]
##  [619] (75.5,78.2] (75.5,78.2] (78.2,80.9] (86.4,89.1] (86.4,89.1] (70,72.7]  
##  [625] (89.1,91.8] (83.6,86.4] (83.6,86.4] (86.4,89.1] (75.5,78.2] (83.6,86.4]
##  [631] (75.5,78.2] (94.5,97.3] (70,72.7]   (86.4,89.1] (89.1,91.8] (86.4,89.1]
##  [637] (89.1,91.8] (94.5,97.3] (91.8,94.5] (97.3,100]  (89.1,91.8] (91.8,94.5]
##  [643] (78.2,80.9] (94.5,97.3] (94.5,97.3] (83.6,86.4] (83.6,86.4] (72.7,75.5]
##  [649] (72.7,75.5] (70,72.7]   (97.3,100]  (75.5,78.2] (72.7,75.5] (80.9,83.6]
##  [655] (72.7,75.5] (70,72.7]   (94.5,97.3] (86.4,89.1] (86.4,89.1] (97.3,100] 
##  [661] (97.3,100]  (70,72.7]   (75.5,78.2] (80.9,83.6] (80.9,83.6] (86.4,89.1]
##  [667] (91.8,94.5] (75.5,78.2] (89.1,91.8] (72.7,75.5] (80.9,83.6] (83.6,86.4]
##  [673] (70,72.7]   (97.3,100]  (70,72.7]   (97.3,100]  (94.5,97.3] (75.5,78.2]
##  [679] (91.8,94.5] (89.1,91.8] (78.2,80.9] (97.3,100]  (75.5,78.2] (91.8,94.5]
##  [685] (70,72.7]   (94.5,97.3] (75.5,78.2] (83.6,86.4] (72.7,75.5] (70,72.7]  
##  [691] (70,72.7]   (72.7,75.5] (91.8,94.5] (89.1,91.8] (70,72.7]   (75.5,78.2]
##  [697] (86.4,89.1] (72.7,75.5] (78.2,80.9] (75.5,78.2] (70,72.7]   (72.7,75.5]
##  [703] (72.7,75.5] (80.9,83.6] (91.8,94.5] (78.2,80.9] (89.1,91.8] (89.1,91.8]
##  [709] (97.3,100]  (70,72.7]   (94.5,97.3] (70,72.7]   (70,72.7]   (91.8,94.5]
##  [715] (70,72.7]   (80.9,83.6] (91.8,94.5] (89.1,91.8] (89.1,91.8] (86.4,89.1]
##  [721] (83.6,86.4] (94.5,97.3] (86.4,89.1] (78.2,80.9] (86.4,89.1] (75.5,78.2]
##  [727] (70,72.7]   (91.8,94.5] (78.2,80.9] (75.5,78.2] (70,72.7]   (86.4,89.1]
##  [733] (72.7,75.5] (72.7,75.5] (72.7,75.5] (94.5,97.3] (75.5,78.2] (80.9,83.6]
##  [739] (72.7,75.5] (72.7,75.5] (80.9,83.6] (78.2,80.9] (97.3,100]  (94.5,97.3]
##  [745] (78.2,80.9] (97.3,100]  (86.4,89.1] (89.1,91.8] (89.1,91.8] (91.8,94.5]
##  [751] (97.3,100]  (72.7,75.5] (89.1,91.8] (80.9,83.6] (91.8,94.5] (89.1,91.8]
##  [757] (97.3,100]  (86.4,89.1] (78.2,80.9] (97.3,100]  (70,72.7]   (83.6,86.4]
##  [763] (91.8,94.5] (97.3,100]  (78.2,80.9] (94.5,97.3] (89.1,91.8] (97.3,100] 
##  [769] (91.8,94.5] (91.8,94.5] (80.9,83.6] (94.5,97.3] (89.1,91.8] (94.5,97.3]
##  [775] (86.4,89.1] (94.5,97.3] (94.5,97.3] (75.5,78.2] (91.8,94.5] (83.6,86.4]
##  [781] (83.6,86.4] (91.8,94.5] (91.8,94.5] (72.7,75.5] (70,72.7]   (94.5,97.3]
##  [787] (91.8,94.5] (72.7,75.5] (80.9,83.6] (83.6,86.4] (97.3,100]  (70,72.7]  
##  [793] (72.7,75.5] (94.5,97.3] (72.7,75.5] (70,72.7]   (83.6,86.4] (91.8,94.5]
##  [799] (89.1,91.8] (70,72.7]   (86.4,89.1] (70,72.7]   (78.2,80.9] (89.1,91.8]
##  [805] (91.8,94.5] (94.5,97.3] (80.9,83.6] (80.9,83.6] (70,72.7]   (70,72.7]  
##  [811] (89.1,91.8] (97.3,100]  (83.6,86.4] (89.1,91.8] (72.7,75.5] (75.5,78.2]
##  [817] (91.8,94.5] (91.8,94.5] (75.5,78.2] (94.5,97.3] (80.9,83.6] (83.6,86.4]
##  [823] (70,72.7]   (86.4,89.1] (70,72.7]   (75.5,78.2] (75.5,78.2] (78.2,80.9]
##  [829] (97.3,100]  (72.7,75.5] (94.5,97.3] (80.9,83.6] (83.6,86.4] (72.7,75.5]
##  [835] (94.5,97.3] (72.7,75.5] (97.3,100]  (86.4,89.1] (94.5,97.3] (89.1,91.8]
##  [841] (80.9,83.6] (89.1,91.8] (97.3,100]  (94.5,97.3] (75.5,78.2] (91.8,94.5]
##  [847] (75.5,78.2] (94.5,97.3] (75.5,78.2] (70,72.7]   (70,72.7]   (83.6,86.4]
##  [853] (75.5,78.2] (80.9,83.6] (80.9,83.6] (94.5,97.3] (80.9,83.6] (83.6,86.4]
##  [859] (70,72.7]   (83.6,86.4] (86.4,89.1] (72.7,75.5] (94.5,97.3] (97.3,100] 
##  [865] (83.6,86.4] (91.8,94.5] (86.4,89.1] (72.7,75.5] (80.9,83.6] (91.8,94.5]
##  [871] (97.3,100]  (89.1,91.8] (80.9,83.6] (91.8,94.5] (80.9,83.6] (94.5,97.3]
##  [877] (80.9,83.6] (70,72.7]   (97.3,100]  (91.8,94.5] (80.9,83.6] (86.4,89.1]
##  [883] (72.7,75.5] (72.7,75.5] (78.2,80.9] (75.5,78.2] (91.8,94.5] (97.3,100] 
##  [889] (70,72.7]   (75.5,78.2] (83.6,86.4] (83.6,86.4] (75.5,78.2] (94.5,97.3]
##  [895] (70,72.7]   (80.9,83.6] (97.3,100]  (72.7,75.5] (89.1,91.8] (78.2,80.9]
##  [901] (94.5,97.3] (83.6,86.4] (75.5,78.2] (94.5,97.3] (83.6,86.4] (72.7,75.5]
##  [907] (83.6,86.4] (75.5,78.2] (97.3,100]  (70,72.7]   (94.5,97.3] (75.5,78.2]
##  [913] (80.9,83.6] (91.8,94.5] (80.9,83.6] (70,72.7]   (86.4,89.1] (80.9,83.6]
##  [919] (94.5,97.3] (86.4,89.1] (72.7,75.5] (97.3,100]  (75.5,78.2] (83.6,86.4]
##  [925] (70,72.7]   (83.6,86.4] (83.6,86.4] (70,72.7]   (86.4,89.1] (75.5,78.2]
##  [931] (86.4,89.1] (72.7,75.5] (80.9,83.6] (94.5,97.3] (75.5,78.2] (97.3,100] 
##  [937] (80.9,83.6] (83.6,86.4] (80.9,83.6] (91.8,94.5] (75.5,78.2] (72.7,75.5]
##  [943] (75.5,78.2] (70,72.7]   (91.8,94.5] (89.1,91.8] (89.1,91.8] (97.3,100] 
##  [949] (89.1,91.8] (72.7,75.5] (94.5,97.3] (83.6,86.4] (91.8,94.5] (91.8,94.5]
##  [955] (83.6,86.4] (78.2,80.9] (75.5,78.2] (72.7,75.5] (86.4,89.1] (78.2,80.9]
##  [961] (86.4,89.1] (83.6,86.4] (80.9,83.6] (94.5,97.3] (94.5,97.3] (78.2,80.9]
##  [967] (86.4,89.1] (83.6,86.4] (78.2,80.9] (89.1,91.8] (78.2,80.9] (80.9,83.6]
##  [973] (94.5,97.3] (83.6,86.4] (78.2,80.9] (72.7,75.5] (80.9,83.6] (94.5,97.3]
##  [979] (94.5,97.3] (94.5,97.3] (91.8,94.5] (91.8,94.5] (72.7,75.5] (91.8,94.5]
##  [985] (94.5,97.3] (94.5,97.3] (94.5,97.3] (78.2,80.9] (75.5,78.2] (75.5,78.2]
##  [991] (72.7,75.5] (86.4,89.1] (80.9,83.6] (72.7,75.5] (86.4,89.1] (72.7,75.5]
##  [997] (72.7,75.5] (91.8,94.5] (86.4,89.1] (86.4,89.1]
## 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]   95
## 2  (72.7,75.5]   89
## 3  (75.5,78.2]  106
## 4  (78.2,80.9]   63
## 5  (80.9,83.6]   98
## 6  (83.6,86.4]  109
## 7  (86.4,89.1]   86
## 8  (89.1,91.8]   73
## 9  (91.8,94.5]   96
## 10 (94.5,97.3]   94
## 11  (97.3,100]   91
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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