——–

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

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  72  72  72  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  73  73  73  73
##   [91]  73  73  73  73  73  73  73  73  73  73  73  73  73  73  73  73  73  73
##  [109]  73  73  73  73  74  74  74  74  74  74  74  74  74  74  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  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  76  76  76  76  76  76
##  [181]  76  76  76  76  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  77  77  77  77
##  [217]  77  77  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  77  77  77  77  77  77  77
##  [253]  77  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  78  78  78  78  78  78  78  78  78  78
##  [289]  78  78  78  78  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  79  79  79  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  80  80  80  80  80  80  80
##  [361]  80  80  80  80  80  80  80  80  80  80  80  80  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  81  81  81  81  81  81  81  81  81  81  81  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  82  82  82  82  82  82  82  82  83  83  83  83  83  83  83
##  [451]  83  83  83  83  83  83  83  83  83  83  83  83  83  83  83  83  83  83
##  [469]  83  83  83  84  84  84  84  84  84  84  84  84  84  84  84  84  84  84
##  [487]  84  84  84  84  84  84  84  84  84  84  84  84  84  84  84  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  85  85  85  85  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  86  86  86  87  87  87  87  87  87  87  87  87  87  87  87
##  [577]  87  87  87  87  87  87  87  87  87  87  87  87  87  87  87  87  87  87
##  [595]  87  87  87  87  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  88  88  88  88  89
##  [631]  89  89  89  89  89  89  89  89  89  89  89  89  89  89  89  89  89  89
##  [649]  89  89  89  89  89  89  89  89  89  89  89  89  89  89  89  89  89  89
##  [667]  89  90  90  90  90  90  90  90  90  90  90  90  90  90  90  90  90  90
##  [685]  90  90  90  90  90  90  90  90  90  90  90  90  90  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]  91  91  91  91  91  91  91  91  91  91  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  92
##  [757]  92  92  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  94  94  94  94  94  94  94  94
##  [793]  94  94  94  94  94  94  94  94  94  94  94  94  94  94  94  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  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  96  96  96  96  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  97  97  97  97  97  97
##  [901]  97  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  98  98  98  98  98  98
##  [937]  98  98  98  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  99  99  99  99  99  99 100 100
##  [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]  212
## 2  (76,82]  231
## 3  (82,88]  186
## 4  (88,94]  178
## 5 (94,100]  193
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] (91.8,94.5] (80.9,83.6] (72.7,75.5] (83.6,86.4] (72.7,75.5]
##    [7] (72.7,75.5] (86.4,89.1] (86.4,89.1] (97.3,100]  (72.7,75.5] (78.2,80.9]
##   [13] (75.5,78.2] (86.4,89.1] (80.9,83.6] (78.2,80.9] (70,72.7]   (89.1,91.8]
##   [19] (89.1,91.8] (72.7,75.5] (75.5,78.2] (80.9,83.6] (70,72.7]   (72.7,75.5]
##   [25] (75.5,78.2] (97.3,100]  (97.3,100]  (75.5,78.2] (75.5,78.2] (78.2,80.9]
##   [31] (94.5,97.3] (89.1,91.8] (89.1,91.8] (78.2,80.9] (86.4,89.1] (89.1,91.8]
##   [37] (80.9,83.6] (83.6,86.4] (91.8,94.5] (89.1,91.8] (97.3,100]  (83.6,86.4]
##   [43] (75.5,78.2] (70,72.7]   (86.4,89.1] (80.9,83.6] (94.5,97.3] (72.7,75.5]
##   [49] (86.4,89.1] (75.5,78.2] (89.1,91.8] (89.1,91.8] (78.2,80.9] (70,72.7]  
##   [55] (97.3,100]  (91.8,94.5] (86.4,89.1] (97.3,100]  (86.4,89.1] (97.3,100] 
##   [61] (91.8,94.5] (75.5,78.2] (72.7,75.5] (75.5,78.2] (94.5,97.3] (86.4,89.1]
##   [67] (86.4,89.1] (72.7,75.5] (80.9,83.6] (97.3,100]  (75.5,78.2] (83.6,86.4]
##   [73] (75.5,78.2] (80.9,83.6] (86.4,89.1] (83.6,86.4] (72.7,75.5] (80.9,83.6]
##   [79] (75.5,78.2] (70,72.7]   (75.5,78.2] (72.7,75.5] (97.3,100]  (78.2,80.9]
##   [85] (91.8,94.5] (78.2,80.9] (86.4,89.1] (91.8,94.5] (70,72.7]   (83.6,86.4]
##   [91] (80.9,83.6] (70,72.7]   (89.1,91.8] (91.8,94.5] (70,72.7]   (72.7,75.5]
##   [97] (83.6,86.4] (94.5,97.3] (78.2,80.9] (78.2,80.9] (72.7,75.5] (75.5,78.2]
##  [103] (78.2,80.9] (86.4,89.1] (70,72.7]   (80.9,83.6] (80.9,83.6] (83.6,86.4]
##  [109] (70,72.7]   (72.7,75.5] (86.4,89.1] (75.5,78.2] (94.5,97.3] (97.3,100] 
##  [115] (80.9,83.6] (94.5,97.3] (97.3,100]  (78.2,80.9] (94.5,97.3] (89.1,91.8]
##  [121] (72.7,75.5] (75.5,78.2] (83.6,86.4] (97.3,100]  (72.7,75.5] (97.3,100] 
##  [127] (86.4,89.1] (75.5,78.2] (86.4,89.1] (78.2,80.9] (83.6,86.4] (97.3,100] 
##  [133] (91.8,94.5] (83.6,86.4] (91.8,94.5] (97.3,100]  (91.8,94.5] (78.2,80.9]
##  [139] (72.7,75.5] (80.9,83.6] (80.9,83.6] (72.7,75.5] (86.4,89.1] (86.4,89.1]
##  [145] (70,72.7]   (78.2,80.9] (72.7,75.5] (78.2,80.9] (80.9,83.6] (70,72.7]  
##  [151] (91.8,94.5] (94.5,97.3] (75.5,78.2] (80.9,83.6] (78.2,80.9] (89.1,91.8]
##  [157] (97.3,100]  (86.4,89.1] (83.6,86.4] (83.6,86.4] (70,72.7]   (97.3,100] 
##  [163] (78.2,80.9] (83.6,86.4] (97.3,100]  (75.5,78.2] (89.1,91.8] (80.9,83.6]
##  [169] (91.8,94.5] (86.4,89.1] (78.2,80.9] (80.9,83.6] (97.3,100]  (72.7,75.5]
##  [175] (94.5,97.3] (97.3,100]  (91.8,94.5] (97.3,100]  (97.3,100]  (75.5,78.2]
##  [181] (80.9,83.6] (70,72.7]   (75.5,78.2] (89.1,91.8] (75.5,78.2] (94.5,97.3]
##  [187] (75.5,78.2] (78.2,80.9] (86.4,89.1] (94.5,97.3] (78.2,80.9] (70,72.7]  
##  [193] (91.8,94.5] (70,72.7]   (91.8,94.5] (72.7,75.5] (91.8,94.5] (94.5,97.3]
##  [199] (75.5,78.2] (70,72.7]   (89.1,91.8] (91.8,94.5] (97.3,100]  (97.3,100] 
##  [205] (89.1,91.8] (72.7,75.5] (78.2,80.9] (75.5,78.2] (83.6,86.4] (83.6,86.4]
##  [211] (72.7,75.5] (83.6,86.4] (75.5,78.2] (75.5,78.2] (97.3,100]  (97.3,100] 
##  [217] (78.2,80.9] (86.4,89.1] (78.2,80.9] (86.4,89.1] (72.7,75.5] (80.9,83.6]
##  [223] (75.5,78.2] (78.2,80.9] (78.2,80.9] (83.6,86.4] (75.5,78.2] (94.5,97.3]
##  [229] (91.8,94.5] (75.5,78.2] (80.9,83.6] (80.9,83.6] (83.6,86.4] (86.4,89.1]
##  [235] (72.7,75.5] (80.9,83.6] (91.8,94.5] (89.1,91.8] (91.8,94.5] (97.3,100] 
##  [241] (94.5,97.3] (97.3,100]  (72.7,75.5] (78.2,80.9] (97.3,100]  (91.8,94.5]
##  [247] (86.4,89.1] (70,72.7]   (72.7,75.5] (97.3,100]  (80.9,83.6] (97.3,100] 
##  [253] (75.5,78.2] (91.8,94.5] (86.4,89.1] (72.7,75.5] (86.4,89.1] (72.7,75.5]
##  [259] (94.5,97.3] (80.9,83.6] (72.7,75.5] (72.7,75.5] (75.5,78.2] (75.5,78.2]
##  [265] (83.6,86.4] (89.1,91.8] (75.5,78.2] (70,72.7]   (94.5,97.3] (94.5,97.3]
##  [271] (86.4,89.1] (94.5,97.3] (86.4,89.1] (75.5,78.2] (75.5,78.2] (70,72.7]  
##  [277] (78.2,80.9] (83.6,86.4] (97.3,100]  (75.5,78.2] (72.7,75.5] (83.6,86.4]
##  [283] (86.4,89.1] (83.6,86.4] (94.5,97.3] (94.5,97.3] (78.2,80.9] (75.5,78.2]
##  [289] (83.6,86.4] (91.8,94.5] (83.6,86.4] (78.2,80.9] (83.6,86.4] (75.5,78.2]
##  [295] (83.6,86.4] (91.8,94.5] (80.9,83.6] (83.6,86.4] (72.7,75.5] (89.1,91.8]
##  [301] (89.1,91.8] (78.2,80.9] (80.9,83.6] (70,72.7]   (86.4,89.1] (83.6,86.4]
##  [307] (94.5,97.3] (94.5,97.3] (78.2,80.9] (97.3,100]  (80.9,83.6] (94.5,97.3]
##  [313] (91.8,94.5] (80.9,83.6] (89.1,91.8] (72.7,75.5] (75.5,78.2] (75.5,78.2]
##  [319] (83.6,86.4] (83.6,86.4] (91.8,94.5] (94.5,97.3] (89.1,91.8] (83.6,86.4]
##  [325] (70,72.7]   (89.1,91.8] (70,72.7]   (86.4,89.1] (80.9,83.6] (86.4,89.1]
##  [331] (78.2,80.9] (78.2,80.9] (83.6,86.4] (75.5,78.2] (94.5,97.3] (75.5,78.2]
##  [337] (86.4,89.1] (80.9,83.6] (86.4,89.1] (83.6,86.4] (75.5,78.2] (80.9,83.6]
##  [343] (80.9,83.6] (89.1,91.8] (83.6,86.4] (89.1,91.8] (75.5,78.2] (94.5,97.3]
##  [349] (91.8,94.5] (78.2,80.9] (75.5,78.2] (80.9,83.6] (72.7,75.5] (86.4,89.1]
##  [355] (83.6,86.4] (72.7,75.5] (97.3,100]  (86.4,89.1] (86.4,89.1] (89.1,91.8]
##  [361] (86.4,89.1] (75.5,78.2] (75.5,78.2] (83.6,86.4] (86.4,89.1] (94.5,97.3]
##  [367] (97.3,100]  (72.7,75.5] (94.5,97.3] (72.7,75.5] (78.2,80.9] (78.2,80.9]
##  [373] (97.3,100]  (70,72.7]   (75.5,78.2] (75.5,78.2] (94.5,97.3] (80.9,83.6]
##  [379] (91.8,94.5] (75.5,78.2] (97.3,100]  (91.8,94.5] (86.4,89.1] (83.6,86.4]
##  [385] (86.4,89.1] (86.4,89.1] (83.6,86.4] (83.6,86.4] (70,72.7]   (83.6,86.4]
##  [391] (80.9,83.6] (97.3,100]  (94.5,97.3] (72.7,75.5] (80.9,83.6] (80.9,83.6]
##  [397] (83.6,86.4] (72.7,75.5] (75.5,78.2] (97.3,100]  (97.3,100]  (75.5,78.2]
##  [403] (75.5,78.2] (89.1,91.8] (70,72.7]   (80.9,83.6] (91.8,94.5] (86.4,89.1]
##  [409] (72.7,75.5] (83.6,86.4] (72.7,75.5] (70,72.7]   (97.3,100]  (78.2,80.9]
##  [415] (83.6,86.4] (89.1,91.8] (86.4,89.1] (91.8,94.5] (75.5,78.2] (70,72.7]  
##  [421] (86.4,89.1] (80.9,83.6] (80.9,83.6] (97.3,100]  (86.4,89.1] (83.6,86.4]
##  [427] (86.4,89.1] (97.3,100]  (94.5,97.3] (70,72.7]   (94.5,97.3] (97.3,100] 
##  [433] (83.6,86.4] (91.8,94.5] (86.4,89.1] (86.4,89.1] (83.6,86.4] (78.2,80.9]
##  [439] (91.8,94.5] (70,72.7]   (78.2,80.9] (72.7,75.5] (83.6,86.4] (78.2,80.9]
##  [445] (86.4,89.1] (86.4,89.1] (72.7,75.5] (86.4,89.1] (97.3,100]  (83.6,86.4]
##  [451] (94.5,97.3] (80.9,83.6] (94.5,97.3] (75.5,78.2] (75.5,78.2] (94.5,97.3]
##  [457] (97.3,100]  (80.9,83.6] (75.5,78.2] (70,72.7]   (97.3,100]  (72.7,75.5]
##  [463] (78.2,80.9] (94.5,97.3] (72.7,75.5] (75.5,78.2] (89.1,91.8] (70,72.7]  
##  [469] (75.5,78.2] (72.7,75.5] (86.4,89.1] (94.5,97.3] (94.5,97.3] (91.8,94.5]
##  [475] (94.5,97.3] (75.5,78.2] (91.8,94.5] (72.7,75.5] (97.3,100]  (83.6,86.4]
##  [481] (78.2,80.9] (75.5,78.2] (75.5,78.2] (70,72.7]   (70,72.7]   (91.8,94.5]
##  [487] (86.4,89.1] (89.1,91.8] (83.6,86.4] (97.3,100]  (83.6,86.4] (70,72.7]  
##  [493] (80.9,83.6] (70,72.7]   (83.6,86.4] (91.8,94.5] (70,72.7]   (97.3,100] 
##  [499] (75.5,78.2] (72.7,75.5] (89.1,91.8] (80.9,83.6] (78.2,80.9] (75.5,78.2]
##  [505] (97.3,100]  (97.3,100]  (94.5,97.3] (72.7,75.5] (86.4,89.1] (91.8,94.5]
##  [511] (91.8,94.5] (72.7,75.5] (86.4,89.1] (80.9,83.6] (97.3,100]  (86.4,89.1]
##  [517] (83.6,86.4] (78.2,80.9] (78.2,80.9] (78.2,80.9] (86.4,89.1] (83.6,86.4]
##  [523] (89.1,91.8] (80.9,83.6] (94.5,97.3] (83.6,86.4] (72.7,75.5] (78.2,80.9]
##  [529] (97.3,100]  (94.5,97.3] (80.9,83.6] (94.5,97.3] (75.5,78.2] (78.2,80.9]
##  [535] (72.7,75.5] (89.1,91.8] (86.4,89.1] (94.5,97.3] (97.3,100]  (83.6,86.4]
##  [541] (75.5,78.2] (70,72.7]   (91.8,94.5] (91.8,94.5] (94.5,97.3] (72.7,75.5]
##  [547] (89.1,91.8] (94.5,97.3] (80.9,83.6] (75.5,78.2] (70,72.7]   (86.4,89.1]
##  [553] (78.2,80.9] (89.1,91.8] (80.9,83.6] (86.4,89.1] (89.1,91.8] (70,72.7]  
##  [559] (72.7,75.5] (75.5,78.2] (83.6,86.4] (94.5,97.3] (80.9,83.6] (91.8,94.5]
##  [565] (86.4,89.1] (78.2,80.9] (97.3,100]  (91.8,94.5] (94.5,97.3] (83.6,86.4]
##  [571] (80.9,83.6] (80.9,83.6] (72.7,75.5] (78.2,80.9] (86.4,89.1] (78.2,80.9]
##  [577] (91.8,94.5] (70,72.7]   (75.5,78.2] (89.1,91.8] (80.9,83.6] (86.4,89.1]
##  [583] (91.8,94.5] (80.9,83.6] (75.5,78.2] (83.6,86.4] (80.9,83.6] (83.6,86.4]
##  [589] (80.9,83.6] (89.1,91.8] (94.5,97.3] (78.2,80.9] (70,72.7]   (89.1,91.8]
##  [595] (91.8,94.5] (83.6,86.4] (75.5,78.2] (70,72.7]   (80.9,83.6] (86.4,89.1]
##  [601] (72.7,75.5] (70,72.7]   (78.2,80.9] (70,72.7]   (70,72.7]   (94.5,97.3]
##  [607] (75.5,78.2] (80.9,83.6] (94.5,97.3] (70,72.7]   (86.4,89.1] (86.4,89.1]
##  [613] (97.3,100]  (80.9,83.6] (70,72.7]   (86.4,89.1] (72.7,75.5] (94.5,97.3]
##  [619] (97.3,100]  (91.8,94.5] (83.6,86.4] (89.1,91.8] (80.9,83.6] (91.8,94.5]
##  [625] (91.8,94.5] (94.5,97.3] (70,72.7]   (80.9,83.6] (97.3,100]  (83.6,86.4]
##  [631] (75.5,78.2] (94.5,97.3] (91.8,94.5] (91.8,94.5] (94.5,97.3] (78.2,80.9]
##  [637] (83.6,86.4] (75.5,78.2] (70,72.7]   (75.5,78.2] (86.4,89.1] (80.9,83.6]
##  [643] (75.5,78.2] (83.6,86.4] (91.8,94.5] (97.3,100]  (86.4,89.1] (78.2,80.9]
##  [649] (91.8,94.5] (83.6,86.4] (75.5,78.2] (78.2,80.9] (72.7,75.5] (80.9,83.6]
##  [655] (94.5,97.3] (89.1,91.8] (78.2,80.9] (91.8,94.5] (72.7,75.5] (80.9,83.6]
##  [661] (94.5,97.3] (86.4,89.1] (94.5,97.3] (83.6,86.4] (72.7,75.5] (86.4,89.1]
##  [667] (83.6,86.4] (80.9,83.6] (80.9,83.6] (83.6,86.4] (83.6,86.4] (78.2,80.9]
##  [673] (86.4,89.1] (91.8,94.5] (70,72.7]   (83.6,86.4] (89.1,91.8] (70,72.7]  
##  [679] (94.5,97.3] (83.6,86.4] (94.5,97.3] (78.2,80.9] (80.9,83.6] (72.7,75.5]
##  [685] (80.9,83.6] (94.5,97.3] (94.5,97.3] (86.4,89.1] (72.7,75.5] (89.1,91.8]
##  [691] (91.8,94.5] (97.3,100]  (72.7,75.5] (91.8,94.5] (91.8,94.5] (78.2,80.9]
##  [697] (97.3,100]  (83.6,86.4] (97.3,100]  (83.6,86.4] (91.8,94.5] (75.5,78.2]
##  [703] (70,72.7]   (89.1,91.8] (75.5,78.2] (86.4,89.1] (72.7,75.5] (94.5,97.3]
##  [709] (86.4,89.1] (94.5,97.3] (91.8,94.5] (80.9,83.6] (97.3,100]  (78.2,80.9]
##  [715] (83.6,86.4] (86.4,89.1] (86.4,89.1] (86.4,89.1] (75.5,78.2] (80.9,83.6]
##  [721] (91.8,94.5] (75.5,78.2] (72.7,75.5] (70,72.7]   (75.5,78.2] (83.6,86.4]
##  [727] (72.7,75.5] (70,72.7]   (75.5,78.2] (75.5,78.2] (80.9,83.6] (89.1,91.8]
##  [733] (94.5,97.3] (78.2,80.9] (72.7,75.5] (89.1,91.8] (78.2,80.9] (97.3,100] 
##  [739] (70,72.7]   (94.5,97.3] (70,72.7]   (80.9,83.6] (83.6,86.4] (75.5,78.2]
##  [745] (86.4,89.1] (94.5,97.3] (97.3,100]  (72.7,75.5] (91.8,94.5] (80.9,83.6]
##  [751] (94.5,97.3] (97.3,100]  (80.9,83.6] (94.5,97.3] (89.1,91.8] (97.3,100] 
##  [757] (70,72.7]   (86.4,89.1] (97.3,100]  (78.2,80.9] (70,72.7]   (75.5,78.2]
##  [763] (80.9,83.6] (91.8,94.5] (70,72.7]   (97.3,100]  (70,72.7]   (78.2,80.9]
##  [769] (86.4,89.1] (80.9,83.6] (78.2,80.9] (72.7,75.5] (83.6,86.4] (75.5,78.2]
##  [775] (80.9,83.6] (80.9,83.6] (86.4,89.1] (97.3,100]  (70,72.7]   (72.7,75.5]
##  [781] (75.5,78.2] (70,72.7]   (83.6,86.4] (75.5,78.2] (91.8,94.5] (91.8,94.5]
##  [787] (72.7,75.5] (86.4,89.1] (86.4,89.1] (72.7,75.5] (80.9,83.6] (97.3,100] 
##  [793] (78.2,80.9] (80.9,83.6] (75.5,78.2] (97.3,100]  (97.3,100]  (94.5,97.3]
##  [799] (70,72.7]   (80.9,83.6] (94.5,97.3] (97.3,100]  (72.7,75.5] (86.4,89.1]
##  [805] (75.5,78.2] (78.2,80.9] (97.3,100]  (80.9,83.6] (97.3,100]  (75.5,78.2]
##  [811] (70,72.7]   (94.5,97.3] (86.4,89.1] (89.1,91.8] (94.5,97.3] (70,72.7]  
##  [817] (97.3,100]  (70,72.7]   (94.5,97.3] (75.5,78.2] (80.9,83.6] (91.8,94.5]
##  [823] (86.4,89.1] (91.8,94.5] (91.8,94.5] (78.2,80.9] (72.7,75.5] (86.4,89.1]
##  [829] (86.4,89.1] (97.3,100]  (70,72.7]   (75.5,78.2] (94.5,97.3] (75.5,78.2]
##  [835] (94.5,97.3] (80.9,83.6] (91.8,94.5] (75.5,78.2] (75.5,78.2] (89.1,91.8]
##  [841] (89.1,91.8] (80.9,83.6] (75.5,78.2] (75.5,78.2] (70,72.7]   (89.1,91.8]
##  [847] (94.5,97.3] (97.3,100]  (72.7,75.5] (75.5,78.2] (89.1,91.8] (75.5,78.2]
##  [853] (89.1,91.8] (70,72.7]   (94.5,97.3] (97.3,100]  (97.3,100]  (80.9,83.6]
##  [859] (75.5,78.2] (97.3,100]  (89.1,91.8] (94.5,97.3] (78.2,80.9] (97.3,100] 
##  [865] (89.1,91.8] (91.8,94.5] (97.3,100]  (78.2,80.9] (89.1,91.8] (75.5,78.2]
##  [871] (78.2,80.9] (97.3,100]  (97.3,100]  (86.4,89.1] (75.5,78.2] (70,72.7]  
##  [877] (80.9,83.6] (94.5,97.3] (80.9,83.6] (72.7,75.5] (91.8,94.5] (94.5,97.3]
##  [883] (89.1,91.8] (97.3,100]  (89.1,91.8] (70,72.7]   (72.7,75.5] (75.5,78.2]
##  [889] (86.4,89.1] (97.3,100]  (72.7,75.5] (97.3,100]  (83.6,86.4] (72.7,75.5]
##  [895] (94.5,97.3] (72.7,75.5] (97.3,100]  (80.9,83.6] (86.4,89.1] (94.5,97.3]
##  [901] (83.6,86.4] (86.4,89.1] (83.6,86.4] (83.6,86.4] (83.6,86.4] (83.6,86.4]
##  [907] (78.2,80.9] (80.9,83.6] (70,72.7]   (94.5,97.3] (70,72.7]   (86.4,89.1]
##  [913] (70,72.7]   (94.5,97.3] (70,72.7]   (80.9,83.6] (78.2,80.9] (78.2,80.9]
##  [919] (72.7,75.5] (91.8,94.5] (97.3,100]  (70,72.7]   (70,72.7]   (72.7,75.5]
##  [925] (89.1,91.8] (94.5,97.3] (78.2,80.9] (91.8,94.5] (75.5,78.2] (97.3,100] 
##  [931] (97.3,100]  (86.4,89.1] (75.5,78.2] (94.5,97.3] (97.3,100]  (80.9,83.6]
##  [937] (78.2,80.9] (75.5,78.2] (70,72.7]   (75.5,78.2] (70,72.7]   (75.5,78.2]
##  [943] (75.5,78.2] (83.6,86.4] (75.5,78.2] (80.9,83.6] (97.3,100]  (72.7,75.5]
##  [949] (89.1,91.8] (94.5,97.3] (86.4,89.1] (91.8,94.5] (80.9,83.6] (89.1,91.8]
##  [955] (89.1,91.8] (97.3,100]  (75.5,78.2] (75.5,78.2] (75.5,78.2] (86.4,89.1]
##  [961] (97.3,100]  (80.9,83.6] (70,72.7]   (83.6,86.4] (91.8,94.5] (70,72.7]  
##  [967] (89.1,91.8] (91.8,94.5] (94.5,97.3] (83.6,86.4] (86.4,89.1] (94.5,97.3]
##  [973] (89.1,91.8] (83.6,86.4] (75.5,78.2] (75.5,78.2] (78.2,80.9] (94.5,97.3]
##  [979] (80.9,83.6] (70,72.7]   (72.7,75.5] (70,72.7]   (94.5,97.3] (94.5,97.3]
##  [985] (72.7,75.5] (78.2,80.9] (83.6,86.4] (80.9,83.6] (70,72.7]   (91.8,94.5]
##  [991] (72.7,75.5] (97.3,100]  (83.6,86.4] (86.4,89.1] (70,72.7]   (72.7,75.5]
##  [997] (83.6,86.4] (80.9,83.6] (86.4,89.1] (94.5,97.3]
## 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]   86
## 2  (72.7,75.5]   88
## 3  (75.5,78.2]  118
## 4  (78.2,80.9]   80
## 5  (80.9,83.6]   99
## 6  (83.6,86.4]   93
## 7  (86.4,89.1]  103
## 8  (89.1,91.8]   63
## 9  (91.8,94.5]   77
## 10 (94.5,97.3]   94
## 11  (97.3,100]   99
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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