Se omiten las tildes y caracteres para evitar errores de edicion.
Utilice
set.seed(12345)
dat<-rnorm(100,50,4.6 )
datos<-round(dat)
datos
## [1] 53 53 49 48 53 42 53 49 49 46 49 58 52 52 47 54 46 48 55 51 54 57 47
## [24] 43 43 58 48 53 53 49 54 60 59 58 51 52 49 42 58 50 55 39 45 54 54 57
## [47] 43 53 53 44 48 59 50 52 47 51 53 54 60 39 51 44 53 57 47 42 54 57 52
## [70] 44 50 46 45 61 56 54 54 46 52 55 53 55 49 61 54 59 53 49 52 54 46 46
## [93] 59 48 45 53 48 60 47 47
##
## Attaching package: 'fdth'
##
## The following objects are masked from 'package:stats':
##
## sd, var
## Class limits f rf rf(%) cf cf(%)
## [39,41) 2 0.02 2 2 2
## [41,44) 9 0.09 9 11 11
## [44,47) 15 0.15 15 26 26
## [47,50) 17 0.17 17 43 43
## [50,53) 11 0.11 11 54 54
## [53,56) 28 0.28 28 82 82
## [56,59) 9 0.09 9 91 91
## [59,62) 9 0.09 9 100 100
## Class limits f rf rf(%) cf cf(%)
## [39,41) 2 0.02 2 2 2
## [41,43) 6 0.06 6 8 8
## [43,46) 6 0.06 6 14 14
## [46,48) 12 0.12 12 26 26
## [48,50) 17 0.17 17 43 43
## [50,52) 11 0.11 11 54 54
## [52,55) 24 0.24 24 78 78
## [55,57) 9 0.09 9 87 87
## [57,59) 8 0.08 8 95 95
## [59,62) 5 0.05 5 100 100
## [1] 53 53 49 48 53 42 53 49 49 46 49 58 52 52 47 54 46 48 55 51 54 57 47
## [24] 43 43 58 48 53 53 49 54 60 59 58 51 52 49 42 58 50 55 39 45 54 54 57
## [47] 43 53 53 44 48 59 50 52 47 51 53 54 60 39 51 44 53 57 47 42 54 57 52
## [70] 44 50 46 45 61 56 54 54 46 52 55 53 55 49 61 54 59 53 49 52 54 46 46
## [93] 59 48 45 53 48 60 47 47
## Class limits f rf rf(%) cf cf(%)
## [10,17) 0 0.00 0 0 0
## [17,24) 0 0.00 0 0 0
## [24,31) 0 0.00 0 0 0
## [31,38) 0 0.00 0 0 0
## [38,45) 11 0.11 11 11 11
## [1] 53 53 49 48 53 42 53 49 49 46 49 58 52 52 47 54 46 48 55 51 54 57 47
## [24] 43 43 58 48 53 53 49 54 60 59 58 51 52 49 42 58 50 55 39 45 54 54 57
## [47] 43 53 53 44 48 59 50 52 47 51 53 54 60 39 51 44 53 57 47 42 54 57 52
## [70] 44 50 46 45 61 56 54 54 46 52 55 53 55 49 61 54 59 53 49 52 54 46 46
## [93] 59 48 45 53 48 60 47 47
## Class limits f rf rf(%) cf cf(%)
## [30,32) 0 0.00 0 0 0
## [32,34) 0 0.00 0 0 0
## [34,36) 0 0.00 0 0 0
## [36,38) 0 0.00 0 0 0
## [38,40) 2 0.02 2 2 2
## [1] 53 53 49 48 53 42 53 49 49 46 49 58 52 52 47 54 46 48 55 51 54 57 47
## [24] 43 43 58 48 53 53 49 54 60 59 58 51 52 49 42 58 50 55 39 45 54 54 57
## [47] 43 53 53 44 48 59 50 52 47 51 53 54 60 39 51 44 53 57 47 42 54 57 52
## [70] 44 50 46 45 61 56 54 54 46 52 55 53 55 49 61 54 59 53 49 52 54 46 46
## [93] 59 48 45 53 48 60 47 47
## Class limits f rf rf(%) cf cf(%)
## [30,32) 0 0.00 0 0 0
## [32,34) 0 0.00 0 0 0
## [34,36) 0 0.00 0 0 0
## [36,38) 0 0.00 0 0 0
## [38,40) 2 0.02 2 2 2
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 39.00 47.00 52.00 51.13 54.00 61.00
round(datos, digits = 2)->rdatos
sort(rdatos)
## [1] 39 39 42 42 42 43 43 43 44 44 44 45 45 45 46 46 46 46 46 46 47 47 47
## [24] 47 47 47 48 48 48 48 48 48 49 49 49 49 49 49 49 49 50 50 50 51 51 51
## [47] 51 52 52 52 52 52 52 52 53 53 53 53 53 53 53 53 53 53 53 53 53 54 54
## [70] 54 54 54 54 54 54 54 54 54 55 55 55 55 56 57 57 57 57 58 58 58 58 59
## [93] 59 59 59 60 60 60 61 61
## 26%
## 47.74
La interpretacion correcta seria: tenemos un 26% de las personas que tienen edades menores a 47.45, y un 74% que tienen edades mayores a 47.45
## 90%
## 58
stem(datos, scale = 3)
##
## The decimal point is at the |
##
## 39 | 00
## 40 |
## 41 |
## 42 | 000
## 43 | 000
## 44 | 000
## 45 | 000
## 46 | 000000
## 47 | 000000
## 48 | 000000
## 49 | 00000000
## 50 | 000
## 51 | 0000
## 52 | 0000000
## 53 | 0000000000000
## 54 | 00000000000
## 55 | 0000
## 56 | 0
## 57 | 0000
## 58 | 0000
## 59 | 0000
## 60 | 000
## 61 | 00
## [1] 52
## [1] 39 61
## [1] 7