——–

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

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  72  72  72  72
##   [73]  72  72  72  72  72  72  72  72  72  72  72  72  72  72  72  72  72  72
##   [91]  72  72  72  72  72  72  72  72  72  72  72  72  72  72  72  72  72  72
##  [109]  72  72  72  72  72  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  73  73  73  73
##  [145]  73  73  73  73  73  73  73  73  73  73  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  75  75  75  75  75  75  75  75  75  75  75  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  76  76  76  76  77  77  77  77
##  [253]  77  77  77  77  77  77  77  77  77  77  77  77  77  77  77  77  77  77
##  [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  78  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  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  81  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  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]  84  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  85  85  85  85
##  [487]  85  85  85  85  85  85  85  85  85  85  85  85  85  85  85  85  85  86
##  [505]  86  86  86  86  86  86  86  86  86  86  86  86  86  86  86  86  86  86
##  [523]  86  86  86  86  86  86  86  86  86  86  87  87  87  87  87  87  87  87
##  [541]  87  87  87  87  87  87  87  87  87  87  87  87  87  87  87  87  87  87
##  [559]  88  88  88  88  88  88  88  88  88  88  88  88  88  88  88  88  88  88
##  [577]  88  88  88  88  88  88  88  88  88  88  88  88  88  88  88  88  89  89
##  [595]  89  89  89  89  89  89  89  89  89  89  89  89  89  89  89  89  89  89
##  [613]  89  89  89  89  89  89  89  89  89  89  89  89  89  90  90  90  90  90
##  [631]  90  90  90  90  90  90  90  90  90  90  90  90  90  90  90  90  90  90
##  [649]  90  90  90  90  90  90  90  90  90  90  90  90  90  90  90  90  90  90
##  [667]  90  90  90  91  91  91  91  91  91  91  91  91  91  91  91  91  91  91
##  [685]  91  91  91  91  91  91  91  91  91  91  91  91  91  92  92  92  92  92
##  [703]  92  92  92  92  92  92  92  92  92  92  92  92  92  92  92  92  92  92
##  [721]  92  92  92  92  92  93  93  93  93  93  93  93  93  93  93  93  93  93
##  [739]  93  93  93  93  93  93  93  93  93  93  93  93  93  93  93  93  93  93
##  [757]  93  93  93  94  94  94  94  94  94  94  94  94  94  94  94  94  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  95  95  95  95  95  95  95  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  96  96  96  96  96  96  96  96  96  96
##  [847]  96  96  96  96  96  96  96  96  96  96  96  96  96  96  96  96  96  96
##  [865]  96  96  96  96  97  97  97  97  97  97  97  97  97  97  97  97  97  97
##  [883]  97  97  97  97  97  97  97  97  97  97  97  97  97  97  97  97  97  97
##  [901]  97  97  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  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]  248
## 2  (76,82]  178
## 3  (82,88]  166
## 4  (88,94]  207
## 5 (94,100]  201
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] (78.2,80.9] (72.7,75.5] (91.8,94.5] (94.5,97.3]
##    [7] (75.5,78.2] (72.7,75.5] (72.7,75.5] (97.3,100]  (70,72.7]   (83.6,86.4]
##   [13] (70,72.7]   (70,72.7]   (75.5,78.2] (80.9,83.6] (83.6,86.4] (72.7,75.5]
##   [19] (70,72.7]   (75.5,78.2] (78.2,80.9] (83.6,86.4] (80.9,83.6] (75.5,78.2]
##   [25] (97.3,100]  (94.5,97.3] (97.3,100]  (78.2,80.9] (91.8,94.5] (72.7,75.5]
##   [31] (86.4,89.1] (72.7,75.5] (86.4,89.1] (94.5,97.3] (70,72.7]   (72.7,75.5]
##   [37] (80.9,83.6] (78.2,80.9] (97.3,100]  (78.2,80.9] (83.6,86.4] (89.1,91.8]
##   [43] (83.6,86.4] (97.3,100]  (78.2,80.9] (89.1,91.8] (70,72.7]   (86.4,89.1]
##   [49] (97.3,100]  (83.6,86.4] (70,72.7]   (86.4,89.1] (86.4,89.1] (83.6,86.4]
##   [55] (70,72.7]   (97.3,100]  (72.7,75.5] (70,72.7]   (86.4,89.1] (83.6,86.4]
##   [61] (94.5,97.3] (94.5,97.3] (70,72.7]   (91.8,94.5] (75.5,78.2] (78.2,80.9]
##   [67] (70,72.7]   (78.2,80.9] (78.2,80.9] (97.3,100]  (91.8,94.5] (83.6,86.4]
##   [73] (70,72.7]   (80.9,83.6] (89.1,91.8] (70,72.7]   (83.6,86.4] (70,72.7]  
##   [79] (72.7,75.5] (70,72.7]   (97.3,100]  (80.9,83.6] (91.8,94.5] (80.9,83.6]
##   [85] (94.5,97.3] (72.7,75.5] (83.6,86.4] (89.1,91.8] (86.4,89.1] (78.2,80.9]
##   [91] (89.1,91.8] (72.7,75.5] (91.8,94.5] (83.6,86.4] (86.4,89.1] (75.5,78.2]
##   [97] (72.7,75.5] (75.5,78.2] (70,72.7]   (86.4,89.1] (72.7,75.5] (94.5,97.3]
##  [103] (70,72.7]   (97.3,100]  (86.4,89.1] (89.1,91.8] (86.4,89.1] (86.4,89.1]
##  [109] (94.5,97.3] (75.5,78.2] (89.1,91.8] (94.5,97.3] (97.3,100]  (70,72.7]  
##  [115] (72.7,75.5] (78.2,80.9] (70,72.7]   (86.4,89.1] (72.7,75.5] (83.6,86.4]
##  [121] (89.1,91.8] (94.5,97.3] (83.6,86.4] (86.4,89.1] (83.6,86.4] (94.5,97.3]
##  [127] (91.8,94.5] (94.5,97.3] (86.4,89.1] (70,72.7]   (75.5,78.2] (94.5,97.3]
##  [133] (91.8,94.5] (94.5,97.3] (91.8,94.5] (89.1,91.8] (91.8,94.5] (80.9,83.6]
##  [139] (70,72.7]   (72.7,75.5] (78.2,80.9] (89.1,91.8] (91.8,94.5] (83.6,86.4]
##  [145] (91.8,94.5] (80.9,83.6] (70,72.7]   (89.1,91.8] (89.1,91.8] (72.7,75.5]
##  [151] (75.5,78.2] (72.7,75.5] (75.5,78.2] (86.4,89.1] (89.1,91.8] (94.5,97.3]
##  [157] (89.1,91.8] (83.6,86.4] (89.1,91.8] (91.8,94.5] (75.5,78.2] (91.8,94.5]
##  [163] (72.7,75.5] (80.9,83.6] (91.8,94.5] (86.4,89.1] (70,72.7]   (97.3,100] 
##  [169] (83.6,86.4] (70,72.7]   (72.7,75.5] (89.1,91.8] (89.1,91.8] (86.4,89.1]
##  [175] (91.8,94.5] (78.2,80.9] (78.2,80.9] (86.4,89.1] (75.5,78.2] (72.7,75.5]
##  [181] (97.3,100]  (86.4,89.1] (75.5,78.2] (91.8,94.5] (75.5,78.2] (70,72.7]  
##  [187] (91.8,94.5] (70,72.7]   (75.5,78.2] (94.5,97.3] (91.8,94.5] (78.2,80.9]
##  [193] (94.5,97.3] (75.5,78.2] (70,72.7]   (89.1,91.8] (70,72.7]   (91.8,94.5]
##  [199] (80.9,83.6] (83.6,86.4] (94.5,97.3] (89.1,91.8] (89.1,91.8] (89.1,91.8]
##  [205] (70,72.7]   (72.7,75.5] (94.5,97.3] (97.3,100]  (70,72.7]   (80.9,83.6]
##  [211] (72.7,75.5] (70,72.7]   (75.5,78.2] (83.6,86.4] (89.1,91.8] (72.7,75.5]
##  [217] (70,72.7]   (80.9,83.6] (70,72.7]   (91.8,94.5] (80.9,83.6] (83.6,86.4]
##  [223] (78.2,80.9] (75.5,78.2] (83.6,86.4] (78.2,80.9] (70,72.7]   (70,72.7]  
##  [229] (75.5,78.2] (72.7,75.5] (72.7,75.5] (75.5,78.2] (80.9,83.6] (80.9,83.6]
##  [235] (72.7,75.5] (86.4,89.1] (91.8,94.5] (83.6,86.4] (70,72.7]   (80.9,83.6]
##  [241] (86.4,89.1] (72.7,75.5] (83.6,86.4] (75.5,78.2] (70,72.7]   (91.8,94.5]
##  [247] (94.5,97.3] (78.2,80.9] (97.3,100]  (80.9,83.6] (70,72.7]   (75.5,78.2]
##  [253] (80.9,83.6] (94.5,97.3] (97.3,100]  (78.2,80.9] (86.4,89.1] (94.5,97.3]
##  [259] (72.7,75.5] (89.1,91.8] (86.4,89.1] (86.4,89.1] (86.4,89.1] (91.8,94.5]
##  [265] (80.9,83.6] (70,72.7]   (70,72.7]   (72.7,75.5] (89.1,91.8] (80.9,83.6]
##  [271] (91.8,94.5] (72.7,75.5] (97.3,100]  (80.9,83.6] (70,72.7]   (86.4,89.1]
##  [277] (75.5,78.2] (72.7,75.5] (86.4,89.1] (97.3,100]  (72.7,75.5] (80.9,83.6]
##  [283] (83.6,86.4] (80.9,83.6] (78.2,80.9] (70,72.7]   (86.4,89.1] (97.3,100] 
##  [289] (83.6,86.4] (94.5,97.3] (75.5,78.2] (80.9,83.6] (91.8,94.5] (75.5,78.2]
##  [295] (78.2,80.9] (94.5,97.3] (78.2,80.9] (86.4,89.1] (94.5,97.3] (75.5,78.2]
##  [301] (94.5,97.3] (86.4,89.1] (70,72.7]   (70,72.7]   (91.8,94.5] (72.7,75.5]
##  [307] (91.8,94.5] (89.1,91.8] (70,72.7]   (78.2,80.9] (80.9,83.6] (75.5,78.2]
##  [313] (83.6,86.4] (89.1,91.8] (94.5,97.3] (78.2,80.9] (89.1,91.8] (75.5,78.2]
##  [319] (91.8,94.5] (97.3,100]  (70,72.7]   (83.6,86.4] (86.4,89.1] (70,72.7]  
##  [325] (72.7,75.5] (80.9,83.6] (97.3,100]  (89.1,91.8] (83.6,86.4] (80.9,83.6]
##  [331] (78.2,80.9] (86.4,89.1] (75.5,78.2] (94.5,97.3] (75.5,78.2] (91.8,94.5]
##  [337] (72.7,75.5] (94.5,97.3] (86.4,89.1] (97.3,100]  (97.3,100]  (94.5,97.3]
##  [343] (75.5,78.2] (72.7,75.5] (70,72.7]   (94.5,97.3] (91.8,94.5] (91.8,94.5]
##  [349] (70,72.7]   (97.3,100]  (86.4,89.1] (72.7,75.5] (97.3,100]  (86.4,89.1]
##  [355] (72.7,75.5] (89.1,91.8] (78.2,80.9] (80.9,83.6] (75.5,78.2] (80.9,83.6]
##  [361] (78.2,80.9] (91.8,94.5] (94.5,97.3] (89.1,91.8] (80.9,83.6] (75.5,78.2]
##  [367] (72.7,75.5] (70,72.7]   (86.4,89.1] (91.8,94.5] (89.1,91.8] (91.8,94.5]
##  [373] (94.5,97.3] (83.6,86.4] (70,72.7]   (97.3,100]  (97.3,100]  (91.8,94.5]
##  [379] (83.6,86.4] (97.3,100]  (97.3,100]  (70,72.7]   (83.6,86.4] (94.5,97.3]
##  [385] (91.8,94.5] (75.5,78.2] (89.1,91.8] (86.4,89.1] (97.3,100]  (97.3,100] 
##  [391] (80.9,83.6] (91.8,94.5] (83.6,86.4] (83.6,86.4] (80.9,83.6] (83.6,86.4]
##  [397] (78.2,80.9] (80.9,83.6] (72.7,75.5] (78.2,80.9] (80.9,83.6] (89.1,91.8]
##  [403] (75.5,78.2] (83.6,86.4] (75.5,78.2] (72.7,75.5] (75.5,78.2] (91.8,94.5]
##  [409] (72.7,75.5] (72.7,75.5] (78.2,80.9] (89.1,91.8] (70,72.7]   (91.8,94.5]
##  [415] (80.9,83.6] (86.4,89.1] (89.1,91.8] (89.1,91.8] (94.5,97.3] (70,72.7]  
##  [421] (86.4,89.1] (86.4,89.1] (86.4,89.1] (72.7,75.5] (78.2,80.9] (86.4,89.1]
##  [427] (89.1,91.8] (70,72.7]   (94.5,97.3] (72.7,75.5] (75.5,78.2] (86.4,89.1]
##  [433] (97.3,100]  (83.6,86.4] (83.6,86.4] (78.2,80.9] (80.9,83.6] (86.4,89.1]
##  [439] (89.1,91.8] (70,72.7]   (80.9,83.6] (86.4,89.1] (80.9,83.6] (83.6,86.4]
##  [445] (94.5,97.3] (94.5,97.3] (75.5,78.2] (86.4,89.1] (91.8,94.5] (70,72.7]  
##  [451] (83.6,86.4] (94.5,97.3] (91.8,94.5] (72.7,75.5] (91.8,94.5] (94.5,97.3]
##  [457] (94.5,97.3] (78.2,80.9] (75.5,78.2] (75.5,78.2] (72.7,75.5] (91.8,94.5]
##  [463] (83.6,86.4] (75.5,78.2] (75.5,78.2] (75.5,78.2] (78.2,80.9] (75.5,78.2]
##  [469] (91.8,94.5] (86.4,89.1] (97.3,100]  (89.1,91.8] (86.4,89.1] (78.2,80.9]
##  [475] (78.2,80.9] (72.7,75.5] (72.7,75.5] (97.3,100]  (70,72.7]   (94.5,97.3]
##  [481] (75.5,78.2] (97.3,100]  (83.6,86.4] (70,72.7]   (72.7,75.5] (75.5,78.2]
##  [487] (94.5,97.3] (78.2,80.9] (86.4,89.1] (97.3,100]  (91.8,94.5] (94.5,97.3]
##  [493] (78.2,80.9] (75.5,78.2] (80.9,83.6] (86.4,89.1] (72.7,75.5] (91.8,94.5]
##  [499] (89.1,91.8] (97.3,100]  (97.3,100]  (94.5,97.3] (72.7,75.5] (91.8,94.5]
##  [505] (91.8,94.5] (86.4,89.1] (70,72.7]   (75.5,78.2] (72.7,75.5] (97.3,100] 
##  [511] (91.8,94.5] (94.5,97.3] (83.6,86.4] (72.7,75.5] (94.5,97.3] (72.7,75.5]
##  [517] (97.3,100]  (70,72.7]   (91.8,94.5] (94.5,97.3] (89.1,91.8] (91.8,94.5]
##  [523] (89.1,91.8] (75.5,78.2] (72.7,75.5] (80.9,83.6] (86.4,89.1] (83.6,86.4]
##  [529] (86.4,89.1] (70,72.7]   (94.5,97.3] (80.9,83.6] (83.6,86.4] (72.7,75.5]
##  [535] (91.8,94.5] (94.5,97.3] (70,72.7]   (91.8,94.5] (78.2,80.9] (72.7,75.5]
##  [541] (70,72.7]   (94.5,97.3] (94.5,97.3] (75.5,78.2] (94.5,97.3] (72.7,75.5]
##  [547] (80.9,83.6] (94.5,97.3] (72.7,75.5] (75.5,78.2] (89.1,91.8] (80.9,83.6]
##  [553] (72.7,75.5] (86.4,89.1] (91.8,94.5] (78.2,80.9] (86.4,89.1] (80.9,83.6]
##  [559] (83.6,86.4] (70,72.7]   (72.7,75.5] (75.5,78.2] (91.8,94.5] (86.4,89.1]
##  [565] (97.3,100]  (70,72.7]   (94.5,97.3] (78.2,80.9] (83.6,86.4] (83.6,86.4]
##  [571] (86.4,89.1] (94.5,97.3] (72.7,75.5] (83.6,86.4] (83.6,86.4] (94.5,97.3]
##  [577] (91.8,94.5] (83.6,86.4] (80.9,83.6] (80.9,83.6] (97.3,100]  (78.2,80.9]
##  [583] (80.9,83.6] (72.7,75.5] (75.5,78.2] (97.3,100]  (91.8,94.5] (97.3,100] 
##  [589] (86.4,89.1] (89.1,91.8] (83.6,86.4] (86.4,89.1] (97.3,100]  (94.5,97.3]
##  [595] (78.2,80.9] (75.5,78.2] (80.9,83.6] (94.5,97.3] (70,72.7]   (86.4,89.1]
##  [601] (72.7,75.5] (70,72.7]   (83.6,86.4] (86.4,89.1] (78.2,80.9] (72.7,75.5]
##  [607] (75.5,78.2] (94.5,97.3] (86.4,89.1] (83.6,86.4] (94.5,97.3] (89.1,91.8]
##  [613] (94.5,97.3] (97.3,100]  (75.5,78.2] (86.4,89.1] (86.4,89.1] (97.3,100] 
##  [619] (78.2,80.9] (80.9,83.6] (83.6,86.4] (94.5,97.3] (70,72.7]   (91.8,94.5]
##  [625] (97.3,100]  (72.7,75.5] (70,72.7]   (70,72.7]   (78.2,80.9] (70,72.7]  
##  [631] (80.9,83.6] (94.5,97.3] (89.1,91.8] (91.8,94.5] (94.5,97.3] (80.9,83.6]
##  [637] (80.9,83.6] (78.2,80.9] (72.7,75.5] (75.5,78.2] (89.1,91.8] (89.1,91.8]
##  [643] (94.5,97.3] (94.5,97.3] (94.5,97.3] (75.5,78.2] (75.5,78.2] (97.3,100] 
##  [649] (89.1,91.8] (91.8,94.5] (70,72.7]   (91.8,94.5] (91.8,94.5] (72.7,75.5]
##  [655] (97.3,100]  (78.2,80.9] (72.7,75.5] (86.4,89.1] (78.2,80.9] (75.5,78.2]
##  [661] (91.8,94.5] (86.4,89.1] (72.7,75.5] (72.7,75.5] (89.1,91.8] (91.8,94.5]
##  [667] (86.4,89.1] (86.4,89.1] (80.9,83.6] (80.9,83.6] (94.5,97.3] (91.8,94.5]
##  [673] (83.6,86.4] (80.9,83.6] (78.2,80.9] (80.9,83.6] (94.5,97.3] (86.4,89.1]
##  [679] (89.1,91.8] (94.5,97.3] (91.8,94.5] (83.6,86.4] (70,72.7]   (75.5,78.2]
##  [685] (86.4,89.1] (70,72.7]   (78.2,80.9] (97.3,100]  (70,72.7]   (70,72.7]  
##  [691] (89.1,91.8] (80.9,83.6] (70,72.7]   (72.7,75.5] (91.8,94.5] (94.5,97.3]
##  [697] (91.8,94.5] (70,72.7]   (75.5,78.2] (86.4,89.1] (70,72.7]   (91.8,94.5]
##  [703] (97.3,100]  (97.3,100]  (72.7,75.5] (91.8,94.5] (94.5,97.3] (70,72.7]  
##  [709] (91.8,94.5] (70,72.7]   (89.1,91.8] (89.1,91.8] (97.3,100]  (78.2,80.9]
##  [715] (75.5,78.2] (97.3,100]  (89.1,91.8] (86.4,89.1] (83.6,86.4] (83.6,86.4]
##  [721] (91.8,94.5] (75.5,78.2] (91.8,94.5] (83.6,86.4] (70,72.7]   (72.7,75.5]
##  [727] (80.9,83.6] (91.8,94.5] (97.3,100]  (97.3,100]  (75.5,78.2] (97.3,100] 
##  [733] (94.5,97.3] (97.3,100]  (97.3,100]  (83.6,86.4] (91.8,94.5] (91.8,94.5]
##  [739] (75.5,78.2] (94.5,97.3] (89.1,91.8] (75.5,78.2] (94.5,97.3] (80.9,83.6]
##  [745] (80.9,83.6] (70,72.7]   (70,72.7]   (97.3,100]  (75.5,78.2] (80.9,83.6]
##  [751] (89.1,91.8] (83.6,86.4] (70,72.7]   (78.2,80.9] (78.2,80.9] (97.3,100] 
##  [757] (91.8,94.5] (97.3,100]  (91.8,94.5] (78.2,80.9] (83.6,86.4] (70,72.7]  
##  [763] (94.5,97.3] (78.2,80.9] (72.7,75.5] (91.8,94.5] (94.5,97.3] (86.4,89.1]
##  [769] (94.5,97.3] (94.5,97.3] (75.5,78.2] (70,72.7]   (80.9,83.6] (91.8,94.5]
##  [775] (86.4,89.1] (80.9,83.6] (70,72.7]   (97.3,100]  (70,72.7]   (94.5,97.3]
##  [781] (70,72.7]   (80.9,83.6] (91.8,94.5] (89.1,91.8] (97.3,100]  (97.3,100] 
##  [787] (80.9,83.6] (78.2,80.9] (97.3,100]  (94.5,97.3] (86.4,89.1] (97.3,100] 
##  [793] (97.3,100]  (78.2,80.9] (78.2,80.9] (78.2,80.9] (97.3,100]  (83.6,86.4]
##  [799] (94.5,97.3] (97.3,100]  (78.2,80.9] (70,72.7]   (97.3,100]  (91.8,94.5]
##  [805] (80.9,83.6] (75.5,78.2] (97.3,100]  (70,72.7]   (97.3,100]  (86.4,89.1]
##  [811] (94.5,97.3] (70,72.7]   (70,72.7]   (70,72.7]   (89.1,91.8] (80.9,83.6]
##  [817] (80.9,83.6] (91.8,94.5] (94.5,97.3] (75.5,78.2] (91.8,94.5] (86.4,89.1]
##  [823] (97.3,100]  (75.5,78.2] (75.5,78.2] (97.3,100]  (91.8,94.5] (91.8,94.5]
##  [829] (70,72.7]   (86.4,89.1] (97.3,100]  (94.5,97.3] (70,72.7]   (89.1,91.8]
##  [835] (70,72.7]   (97.3,100]  (83.6,86.4] (89.1,91.8] (83.6,86.4] (75.5,78.2]
##  [841] (91.8,94.5] (83.6,86.4] (83.6,86.4] (75.5,78.2] (97.3,100]  (91.8,94.5]
##  [847] (89.1,91.8] (91.8,94.5] (86.4,89.1] (94.5,97.3] (89.1,91.8] (80.9,83.6]
##  [853] (86.4,89.1] (72.7,75.5] (97.3,100]  (75.5,78.2] (83.6,86.4] (75.5,78.2]
##  [859] (78.2,80.9] (80.9,83.6] (75.5,78.2] (94.5,97.3] (70,72.7]   (86.4,89.1]
##  [865] (94.5,97.3] (97.3,100]  (89.1,91.8] (91.8,94.5] (83.6,86.4] (94.5,97.3]
##  [871] (80.9,83.6] (97.3,100]  (72.7,75.5] (72.7,75.5] (75.5,78.2] (97.3,100] 
##  [877] (72.7,75.5] (97.3,100]  (83.6,86.4] (97.3,100]  (72.7,75.5] (97.3,100] 
##  [883] (86.4,89.1] (97.3,100]  (75.5,78.2] (94.5,97.3] (80.9,83.6] (83.6,86.4]
##  [889] (72.7,75.5] (80.9,83.6] (86.4,89.1] (70,72.7]   (91.8,94.5] (72.7,75.5]
##  [895] (72.7,75.5] (80.9,83.6] (91.8,94.5] (80.9,83.6] (94.5,97.3] (94.5,97.3]
##  [901] (75.5,78.2] (91.8,94.5] (80.9,83.6] (78.2,80.9] (75.5,78.2] (78.2,80.9]
##  [907] (72.7,75.5] (91.8,94.5] (97.3,100]  (89.1,91.8] (89.1,91.8] (91.8,94.5]
##  [913] (89.1,91.8] (89.1,91.8] (72.7,75.5] (91.8,94.5] (72.7,75.5] (70,72.7]  
##  [919] (70,72.7]   (86.4,89.1] (94.5,97.3] (86.4,89.1] (91.8,94.5] (72.7,75.5]
##  [925] (72.7,75.5] (97.3,100]  (70,72.7]   (94.5,97.3] (80.9,83.6] (83.6,86.4]
##  [931] (80.9,83.6] (97.3,100]  (97.3,100]  (94.5,97.3] (86.4,89.1] (94.5,97.3]
##  [937] (72.7,75.5] (72.7,75.5] (72.7,75.5] (94.5,97.3] (86.4,89.1] (83.6,86.4]
##  [943] (75.5,78.2] (72.7,75.5] (83.6,86.4] (97.3,100]  (75.5,78.2] (91.8,94.5]
##  [949] (72.7,75.5] (86.4,89.1] (70,72.7]   (83.6,86.4] (97.3,100]  (97.3,100] 
##  [955] (72.7,75.5] (94.5,97.3] (89.1,91.8] (83.6,86.4] (97.3,100]  (70,72.7]  
##  [961] (80.9,83.6] (80.9,83.6] (97.3,100]  (94.5,97.3] (94.5,97.3] (72.7,75.5]
##  [967] (91.8,94.5] (72.7,75.5] (72.7,75.5] (80.9,83.6] (89.1,91.8] (89.1,91.8]
##  [973] (70,72.7]   (70,72.7]   (94.5,97.3] (83.6,86.4] (97.3,100]  (70,72.7]  
##  [979] (86.4,89.1] (97.3,100]  (89.1,91.8] (70,72.7]   (91.8,94.5] (83.6,86.4]
##  [985] (86.4,89.1] (94.5,97.3] (83.6,86.4] (72.7,75.5] (70,72.7]   (72.7,75.5]
##  [991] (72.7,75.5] (70,72.7]   (78.2,80.9] (80.9,83.6] (83.6,86.4] (91.8,94.5]
##  [997] (86.4,89.1] (83.6,86.4] (70,72.7]   (75.5,78.2]
## 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]  113
## 2  (72.7,75.5]  102
## 3  (75.5,78.2]   87
## 4  (78.2,80.9]   66
## 5  (80.9,83.6]   82
## 6  (83.6,86.4]   82
## 7  (86.4,89.1]   93
## 8  (89.1,91.8]   72
## 9  (91.8,94.5]  102
## 10 (94.5,97.3]  103
## 11  (97.3,100]   98
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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