Trabajo
Yuliana Hoyos Tapias y Laura Daniela Cedeño
2025-05-29
1. Tabla de Contenido
Introducción a R
RStudio es un entorno de desarrollo integrado (IDE) para el lenguaje de programación R, que se usa principalmente en estadística, ciencia de datos y análisis cuantitativo. Lo que hace RStudio es facilitar la escritura de código en R, la ejecución de scripts, la visualización de gráficos y el manejo de datos de forma más organizada y visualmente accesible.
RStudio ofrece una interfaz dividida en paneles donde puedes ver tu código, tus variables, gráficos y archivos al mismo tiempo. Esto mejora la eficiencia del trabajo analítico, especialmente en proyectos de análisis de datos complejos, modelado estadístico y visualización.
Crear vectores
#crear un vector cuantitativo o numérico
edad<-c(20,25,30,22,20,32,24)
estatura<-c(1.70,1.50,1.65,1,55)
#crear un vector cualitativo
estatura3<-c('alto','bajo','mediano')Crear vectores aleatorios
#crea un vector aleaorio con numeros decimales
vector_aleatorio<- runif(5, min = 0, max = 100)
print(vector_aleatorio)## [1] 21.664787 9.627161 36.639245 25.599806 6.460969#crea un vector aleaorio con numeros enteros
vector_aleatorio2<-sample(1:100, 6, replace=TRUE)
print(vector_aleatorio2)## [1] 29 45 15 24 55 59 # crea solo valores enteros
vector_aleatorio4<-sample.int(18,45,size=5)
#crea un vecto co elementos aleatorios definidos
generos<-sample(c("M","F","O"),10,replace = TRUE)
#"replace = TRUE": indica si el vector puede tener elementos repetidos
#sample: se le puede pedir cialquier tipo de datos
#sample.int: solo se le pueden pedir entrosCreación de una Matriz
#crea una matriz
matriz<- matrix(1:4, nrow = 2, ncol = 2)
print(matriz)## [,1] [,2]
## [1,] 1 3
## [2,] 2 4# se escribe antes de crear daos aleatorios para fijarlos
set.seed(123)
#crea un vector aleatorio de numeros decimales los cuales se redondean con round
edad<-round(runif(6, min=18, max=65))
print(edad)## [1] 32 55 37 60 62 20Operaciones basicas suma y resta
#Suma
#print me permite vizualizar resultado de un objeto o expresión
x=1
y=2
x+y## [1] 3print(x+y)## [1] 3x=1
y=2
x-y## [1] -1print(x-y)## [1] -1#paste es una funcion para concatenar variables categoricas
k="karol"
t="tiene 30 años"
print(paste(k,t)) ## [1] "karol tiene 30 años"#print(paste(k,"",w))
#print(paste(k,w,"\n"))
#paste no se usa para variables numéricasCrear textos con dos variables
#sprintf crea textos utilizando variables donde una es cuantitativa y otra cualitativa donde no se pueden sumar.
edad=20
nombre="Daniela"
print(paste(nombre, "tiene",edad, "años"))## [1] "Daniela tiene 20 años"sprintf("%s tiene %f años",nombre,edad)## [1] "Daniela tiene 20.000000 años"Data frame
#Cada vector debe contener la misma cantidad de objetos o variables
edad<-c(20,25,26,28,27,26,20)
nota<-c(3.5,2.5,5,2.8,3.2,3,5)
materia<-c("algebra","fundamentos","R","Ecuaciones","Grupos","Anillos","caos")
datos<-data.frame(edad,nota,materia)
datos## edad nota materia
## 1 20 3.5 algebra
## 2 25 2.5 fundamentos
## 3 26 5.0 R
## 4 28 2.8 Ecuaciones
## 5 27 3.2 Grupos
## 6 26 3.0 Anillos
## 7 20 5.0 caosEliminar una columna de un data frame
Nombre<-c("Maura","Camila","Johan S","Elkin","Alejandro","Yandri","Nicolas","Dirley","William","Daniela","Steven","Yuliana","Karen","Jose","Santiago","Johan","Santiago","Daniel")
Edad<-c(20,21,21,18,17,19,20,19,24,18,22,20,19,21,20,19,20,19)
Promedio<-c(3.5,3.5,3.5,3.3,3.3,3.92,3.74,3.6,3.5,3.2,3.3,3.3,3.5,3.4,3.5,3.9,3.7,3.7)
Semestre<-c(7,8,7,3,3,7,7,7,10,7,6,8,7,7,5,5,6,5)
Nivelación<-c("si","no","no","no","no","si","si","no","no","no","no","no","no","no","no","si","no","si")
datos<-data.frame(Nombre,Edad,Promedio,Semestre,Nivelación)
datos## Nombre Edad Promedio Semestre Nivelación
## 1 Maura 20 3.50 7 si
## 2 Camila 21 3.50 8 no
## 3 Johan S 21 3.50 7 no
## 4 Elkin 18 3.30 3 no
## 5 Alejandro 17 3.30 3 no
## 6 Yandri 19 3.92 7 si
## 7 Nicolas 20 3.74 7 si
## 8 Dirley 19 3.60 7 no
## 9 William 24 3.50 10 no
## 10 Daniela 18 3.20 7 no
## 11 Steven 22 3.30 6 no
## 12 Yuliana 20 3.30 8 no
## 13 Karen 19 3.50 7 no
## 14 Jose 21 3.40 7 no
## 15 Santiago 20 3.50 5 no
## 16 Johan 19 3.90 5 si
## 17 Santiago 20 3.70 6 no
## 18 Daniel 19 3.70 5 si#Nombre de mi data$Nombre columna a eliminar <- Null
datos$Nivelación<-NULL
datos## Nombre Edad Promedio Semestre
## 1 Maura 20 3.50 7
## 2 Camila 21 3.50 8
## 3 Johan S 21 3.50 7
## 4 Elkin 18 3.30 3
## 5 Alejandro 17 3.30 3
## 6 Yandri 19 3.92 7
## 7 Nicolas 20 3.74 7
## 8 Dirley 19 3.60 7
## 9 William 24 3.50 10
## 10 Daniela 18 3.20 7
## 11 Steven 22 3.30 6
## 12 Yuliana 20 3.30 8
## 13 Karen 19 3.50 7
## 14 Jose 21 3.40 7
## 15 Santiago 20 3.50 5
## 16 Johan 19 3.90 5
## 17 Santiago 20 3.70 6
## 18 Daniel 19 3.70 5Agregar un nuevo dato a mi data frame
datos <- data.frame(
Nombre = c("Maura", "Camila", "Johan", "Elkin", "Alejandro", "Yandri", "Nicolas", "Dirley", "William",
"Daniela", "Steven", "Yuliana", "Karen", "Jose", "Santiago", "Johan", "Santiago", "Daniel"),
Edad = c(20,21,21,18,17,19,20,19,24,18,22,20,19,21,20,19,20,19),
Promedio = c(3.5,3.5,3.5,3.5,3.3,3.3,3.92,3.74,3.6,3.5,3.2,3.3,3.3,3.5,3.4,3.5,3.9,3.7),
Semestre = c(7,8,7,3,3,7,7,7,10,7,6,8,7,7,5,5,6,5),
Nivelación = c("sí", "no", "no", "no", "no", "sí", "no", "no", "no", "no", "no", "no", "sí", "no", "no", "no", "no", "no")
)
#En este caso colocamos el nombre del nuevo dato a agregar, y <-data.frame y luego ya colocamos los datos de mi data frame, depues utilizamos el codigo rbind
#rbind:Sirve para agregar una nueva fila
Saraí <- data.frame(Nombre="Saraí", Edad=21, Promedio=3.8, Semestre=9, Nivelación="no")
datos <- rbind(datos, Saraí)
datos## Nombre Edad Promedio Semestre Nivelación
## 1 Maura 20 3.50 7 sí
## 2 Camila 21 3.50 8 no
## 3 Johan 21 3.50 7 no
## 4 Elkin 18 3.50 3 no
## 5 Alejandro 17 3.30 3 no
## 6 Yandri 19 3.30 7 sí
## 7 Nicolas 20 3.92 7 no
## 8 Dirley 19 3.74 7 no
## 9 William 24 3.60 10 no
## 10 Daniela 18 3.50 7 no
## 11 Steven 22 3.20 6 no
## 12 Yuliana 20 3.30 8 no
## 13 Karen 19 3.30 7 sí
## 14 Jose 21 3.50 7 no
## 15 Santiago 20 3.40 5 no
## 16 Johan 19 3.50 5 no
## 17 Santiago 20 3.90 6 no
## 18 Daniel 19 3.70 5 no
## 19 Saraí 21 3.80 9 no#row.names se utiliza para cambiar el número o nombre en caso dado de uno de los datos dados
row.names(datos)[12]<-(20211195727)
datos## Nombre Edad Promedio Semestre Nivelación
## 1 Maura 20 3.50 7 sí
## 2 Camila 21 3.50 8 no
## 3 Johan 21 3.50 7 no
## 4 Elkin 18 3.50 3 no
## 5 Alejandro 17 3.30 3 no
## 6 Yandri 19 3.30 7 sí
## 7 Nicolas 20 3.92 7 no
## 8 Dirley 19 3.74 7 no
## 9 William 24 3.60 10 no
## 10 Daniela 18 3.50 7 no
## 11 Steven 22 3.20 6 no
## 20211195727 Yuliana 20 3.30 8 no
## 13 Karen 19 3.30 7 sí
## 14 Jose 21 3.50 7 no
## 15 Santiago 20 3.40 5 no
## 16 Johan 19 3.50 5 no
## 17 Santiago 20 3.90 6 no
## 18 Daniel 19 3.70 5 no
## 19 Saraí 21 3.80 9 no#También lo podemos hacer de la siguiente manera, colocando el número del dato que se quiere cmabiar y el numero de la columna
datos[12,1]<-"Yul"
datos## Nombre Edad Promedio Semestre Nivelación
## 1 Maura 20 3.50 7 sí
## 2 Camila 21 3.50 8 no
## 3 Johan 21 3.50 7 no
## 4 Elkin 18 3.50 3 no
## 5 Alejandro 17 3.30 3 no
## 6 Yandri 19 3.30 7 sí
## 7 Nicolas 20 3.92 7 no
## 8 Dirley 19 3.74 7 no
## 9 William 24 3.60 10 no
## 10 Daniela 18 3.50 7 no
## 11 Steven 22 3.20 6 no
## 20211195727 Yul 20 3.30 8 no
## 13 Karen 19 3.30 7 sí
## 14 Jose 21 3.50 7 no
## 15 Santiago 20 3.40 5 no
## 16 Johan 19 3.50 5 no
## 17 Santiago 20 3.90 6 no
## 18 Daniel 19 3.70 5 no
## 19 Saraí 21 3.80 9 no#Para agregar una nueva columna escribimos el nombre de nuestra data $ y el nombre de la nueva columna junto a sus datos.
datos$Numero.hijos<-c(0,1,2,3,4,5,1,2,3,0,1,2,3,0,1,2,3,2,0)
datos## Nombre Edad Promedio Semestre Nivelación Numero.hijos
## 1 Maura 20 3.50 7 sí 0
## 2 Camila 21 3.50 8 no 1
## 3 Johan 21 3.50 7 no 2
## 4 Elkin 18 3.50 3 no 3
## 5 Alejandro 17 3.30 3 no 4
## 6 Yandri 19 3.30 7 sí 5
## 7 Nicolas 20 3.92 7 no 1
## 8 Dirley 19 3.74 7 no 2
## 9 William 24 3.60 10 no 3
## 10 Daniela 18 3.50 7 no 0
## 11 Steven 22 3.20 6 no 1
## 20211195727 Yul 20 3.30 8 no 2
## 13 Karen 19 3.30 7 sí 3
## 14 Jose 21 3.50 7 no 0
## 15 Santiago 20 3.40 5 no 1
## 16 Johan 19 3.50 5 no 2
## 17 Santiago 20 3.90 6 no 3
## 18 Daniel 19 3.70 5 no 2
## 19 Saraí 21 3.80 9 no 0Instalación de paquetes
#install.packages("dplyr")
#library(dplyr)
library(dplyr)##
## Adjuntando el paquete: 'dplyr'## The following objects are masked from 'package:stats':
##
## filter, lag## The following objects are masked from 'package:base':
##
## intersect, setdiff, setequal, uniondf <- data.frame(Nombre = c("Ana", "Luis", "Carlos"), Edad = c(25, 30, 22))
df_filtrado <- df %>% filter(Edad > 24)
print(df_filtrado)## Nombre Edad
## 1 Ana 25
## 2 Luis 30Crear una lista en R con list()
df <- list(
numeros = c(1, 2, 3, 4, 5),
nombres = c("Ana", "Luis", "Carlos"),
matriz = matrix(1:9, nrow = 3)
)
Mi_lista<- list(vector=sample(1:10,5, replace=TRUE),matris1 <- matrix(1:4, nrow = 2, ncol = 2))
Mi_lista## $vector
## [1] 2 6 5 4 6
##
## [[2]]
## [,1] [,2]
## [1,] 1 3
## [2,] 2 4Filtrar Datos
library(dplyr)
#Filtrar datos de una data df es el nombre de la data
datos_filtrado <- datos %>% filter(Promedio > 3.5)
Nombre<-c("Maura","Camila","Johan S","Elkin","Alejandro","Yandri","Nicolas","Dirley","William","Daniela","Steven","Yuliana","Karen","Jose","Santiago","Johan","Santiago","Daniel")
Edad<-c(20,21,21,18,17,19,20,19,24,18,22,20,19,21,20,19,20,19)
Promedio<-c(3.5,3.5,3.5,3.3,3.3,3.92,3.74,3.6,3.5,3.2,3.3,3.3,3.5,3.4,3.5,3.9,3.7,3.7)
Semestre<-c(7,8,7,3,3,7,7,7,10,7,6,8,7,7,5,5,6,5)
Nivelación<-c("si","no","no","no","no","si","si","no","no","no","no","no","no","no","no","si","no","si")
datos<-data.frame(Nombre,Edad,Promedio,Semestre,Nivelación)
datos_filtrado## Nombre Edad Promedio Semestre Nivelación Numero.hijos
## 7 Nicolas 20 3.92 7 no 1
## 8 Dirley 19 3.74 7 no 2
## 9 William 24 3.60 10 no 3
## 17 Santiago 20 3.90 6 no 3
## 18 Daniel 19 3.70 5 no 2
## 19 Saraí 21 3.80 9 no 0Manejo de valores faltantes
df <- data.frame(Nombre = c("Ana", "Luis", "Carlos"), Edad = c(25, NA, 22))
df$Edad[is.na(df$Edad)] <- mean(df$Edad, na.rm = TRUE)
print(df)## Nombre Edad
## 1 Ana 25.0
## 2 Luis 23.5
## 3 Carlos 22.0Limpieza de datos
# Eliminar filas con valores faltantes
df <- na.omit(df)
# Reemplazar valores NA con la mediana
df$Edad[is.na(df$Edad)] <- median(df$Edad, na.rm = TRUE)
# Convertir caracteres a minúsculas
df$Nombre <- tolower(df$Nombre)
print(df)## Nombre Edad
## 1 ana 25.0
## 2 luis 23.5
## 3 carlos 22.0Estadistica Descriptiva
La estadística descriptiva es una rama de la estadística que se encarga de organizar, resumir y presentar datos de manera significativa, utilizando medidas de tendencia central, tablas o gráficos. Su objetivo es describir las características principales de un conjunto de datos sin hacer inferencias o conclusiones sobre una población más amplia.
Cargar una base de Datos
# Cargar el dataset 'mtcars' incorporado en R
data(mtcars)
head(mtcars)## mpg cyl disp hp drat wt qsec vs am gear carb
## Mazda RX4 21.0 6 160 110 3.90 2.620 16.46 0 1 4 4
## Mazda RX4 Wag 21.0 6 160 110 3.90 2.875 17.02 0 1 4 4
## Datsun 710 22.8 4 108 93 3.85 2.320 18.61 1 1 4 1
## Hornet 4 Drive 21.4 6 258 110 3.08 3.215 19.44 1 0 3 1
## Hornet Sportabout 18.7 8 360 175 3.15 3.440 17.02 0 0 3 2
## Valiant 18.1 6 225 105 2.76 3.460 20.22 1 0 3 1#cargar el dataset a traves de un url
url<-'https://raw.githubusercontent.com/fhernanb/datos/master/babies.txt'
D.f<- read.table(url, header=TRUE, sep='\t')
D.f## bwt gestation parity age height weight smoke
## 1 120 284 First born 27 62 100 Not
## 2 113 282 First born 33 64 135 Not
## 3 128 279 First born 28 64 115 Yes
## 4 123 NA First born 36 69 190 Not
## 5 108 282 First born 23 67 125 Yes
## 6 136 286 First born 25 62 93 Not
## 7 138 244 First born 33 62 178 Not
## 8 132 245 First born 23 65 140 Not
## 9 120 289 First born 25 62 125 Not
## 10 143 299 First born 30 66 136 Yes
## 11 140 351 First born 27 68 120 Not
## 12 144 282 First born 32 64 124 Yes
## 13 141 279 First born 23 63 128 Yes
## 14 110 281 First born 36 61 99 Yes
## 15 114 273 First born 30 63 154 Not
## 16 115 285 First born 38 63 130 Not
## 17 92 255 First born 25 65 125 Yes
## 18 115 261 First born 33 60 125 Yes
## 19 144 261 First born 33 68 170 Not
## 20 119 288 First born 43 66 142 Yes
## 21 105 270 First born 22 56 93 Not
## 22 115 274 First born 27 67 175 Yes
## 23 137 287 First born 25 66 145 Not
## 24 122 276 First born 30 68 182 Not
## 25 131 294 First born 23 65 122 Not
## 26 103 261 First born 27 65 112 Yes
## 27 146 280 First born 26 58 106 Not
## 28 114 266 First born 20 65 175 Yes
## 29 125 292 First born 32 65 125 Not
## 30 114 274 First born 28 66 132 Yes
## 31 122 270 First born 26 61 105 Not
## 32 93 278 First born 34 61 146 Not
## 33 130 268 First born 30 66 123 Not
## 34 119 275 First born 23 60 105 Not
## 35 113 281 First born 24 65 120 Not
## 36 134 283 First born 22 67 130 Not
## 37 107 279 First born 24 63 115 Not
## 38 134 288 First born 23 63 92 Yes
## 39 122 267 First born 27 65 101 Yes
## 40 128 282 First born 31 65 NA Not
## 41 129 293 First born 30 61 160 Not
## 42 110 278 First born 23 63 177 Not
## 43 138 302 First born 26 NA NA Yes
## 44 111 270 First born 27 61 119 Not
## 45 87 248 First born 37 65 130 Yes
## 46 143 274 First born 27 63 110 Yes
## 47 155 294 First born 32 66 150 Not
## 48 110 272 First born 25 60 90 Not
## 49 122 275 First born 26 66 147 Not
## 50 145 291 First born 26 63 119 Yes
## 51 115 258 First born 26 62 130 Not
## 52 108 283 First born 31 65 148 Yes
## 53 102 282 First born 28 61 110 Not
## 54 143 286 First born 31 64 126 Not
## 55 146 267 First born 30 67 132 Not
## 56 124 275 First born 22 60 130 Not
## 57 124 278 First born 26 70 145 Yes
## 58 145 257 First born 33 65 140 Not
## 59 106 273 First born 28 60 116 Not
## 60 75 232 First born 33 61 110 Not
## 61 107 273 First born 24 61 96 Not
## 62 124 288 First born 22 67 118 Not
## 63 122 280 First born 23 65 125 Yes
## 64 101 245 First born 23 63 130 Yes
## 65 128 283 First born 28 63 125 Yes
## 66 104 282 First born 36 65 115 Yes
## 67 97 246 First born 37 63 150 Not
## 68 137 274 First born 26 69 137 Yes
## 69 103 273 First born 31 63 170 Yes
## 70 142 276 First born 38 63 170 Not
## 71 130 289 First born 27 66 130 Not
## 72 156 292 First born 26 63 118 Not
## 73 133 284 First born 25 66 125 Yes
## 74 120 274 First born 24 62 120 Not
## 75 91 270 First born 24 60 149 Yes
## 76 127 274 First born 21 62 110 Not
## 77 153 286 First born 26 63 107 Yes
## 78 121 276 First born 39 63 130 Not
## 79 120 277 First born 27 63 126 Not
## 80 99 272 First born 27 62 103 Yes
## 81 149 293 First born 35 65 116 Not
## 82 129 280 First born 23 64 104 Not
## 83 139 292 First born 25 68 135 Not
## 84 114 274 First born 33 67 148 Yes
## 85 138 287 First born 30 66 145 Not
## 86 129 274 First born 29 71 NA Yes
## 87 138 294 First born 32 65 117 Not
## 88 131 296 First born 37 63 143 Not
## 89 125 305 First born 22 70 196 Yes
## 90 114 NA First born 24 67 113 Yes
## 91 128 281 First born 33 59 117 Not
## 92 134 268 First born 28 62 112 Not
## 93 114 271 First born 27 60 104 Not
## 94 92 NA First born 31 67 130 Not
## 95 85 278 First born 23 61 103 Yes
## 96 135 282 First born 22 64 100 Not
## 97 87 255 First born 28 61 100 Yes
## 98 125 302 First born 37 62 162 Not
## 99 128 NA First born 35 62 110 Not
## 100 105 254 First born 29 64 137 Not
## 101 120 279 First born 27 60 121 Yes
## 102 119 274 First born 33 64 120 Not
## 103 116 286 First born 24 61 NA Not
## 104 107 280 First born 36 65 117 Yes
## 105 119 273 First born 24 61 108 Yes
## 106 133 279 First born 37 66 140 Not
## 107 155 287 First born 33 66 143 Not
## 108 126 273 First born 22 65 150 Not
## 109 129 303 First born 27 64 125 Not
## 110 137 274 First born 29 65 154 Not
## 111 103 269 First born 26 65 NA Yes
## 112 125 302 First born 28 65 125 Not
## 113 91 255 First born 19 67 136 Yes
## 114 134 293 First born 21 65 NA Not
## 115 95 279 First born 22 66 145 Yes
## 116 118 276 First born 29 64 114 Not
## 117 141 278 First born 33 66 109 Yes
## 118 131 283 First born 25 67 215 Not
## 119 121 264 First born 32 66 145 Not
## 120 100 243 First born 39 65 170 Yes
## 121 131 288 First born 24 61 103 Not
## 122 118 284 First born 26 66 133 Not
## 123 152 288 First born 35 67 130 Not
## 124 121 284 First born 34 69 155 Not
## 125 117 276 First born 31 69 150 Not
## 126 115 283 First born 25 61 150 Yes
## 127 112 277 First born 23 65 110 Not
## 128 94 267 First born 30 62 120 Yes
## 129 109 272 First born 35 66 154 Not
## 130 132 225 First born 28 67 148 Not
## 131 117 278 First born 25 62 103 Not
## 132 101 266 First born 20 67 110 Yes
## 133 112 294 First born 25 64 125 Yes
## 134 128 283 First born 24 60 100 Not
## 135 128 279 First born 25 66 147 Yes
## 136 117 258 First born 31 64 120 Not
## 137 134 278 First born 24 69 135 Not
## 138 127 284 First born 28 65 145 Not
## 139 93 269 First born 21 65 104 Yes
## 140 122 275 First born 27 65 165 Not
## 141 100 265 First born 39 62 107 Yes
## 142 147 293 First born 32 65 123 Not
## 143 120 299 First born 25 65 110 Not
## 144 144 277 First born 30 63 127 Not
## 145 105 268 First born 32 61 115 Yes
## 146 136 276 First born 23 66 155 Not
## 147 102 262 First born 24 63 125 Not
## 148 160 300 First born 29 71 175 Yes
## 149 113 275 First born 24 68 140 Yes
## 150 126 282 First born 38 66 250 Not
## 151 126 271 First born 29 68 148 Not
## 152 115 278 First born 29 61 128 Not
## 153 127 336 First born 29 NA NA Not
## 154 119 284 First born 20 66 132 Not
## 155 129 NA First born 23 NA NA Yes
## 156 123 318 First born 21 64 152 Not
## 157 118 282 First born 22 68 135 Yes
## 158 133 287 First born 24 60 104 Yes
## 159 105 281 First born 39 61 NA Not
## 160 134 290 First born 22 60 121 Not
## 161 144 288 First born 21 67 111 Not
## 162 111 273 First born 43 62 138 Not
## 163 125 262 First born 36 66 190 Not
## 164 135 296 First born 30 63 123 Not
## 165 134 289 First born 22 63 125 Not
## 166 116 289 First born 22 65 160 Yes
## 167 129 291 First born 29 69 123 Not
## 168 113 301 First born 26 67 105 Yes
## 169 131 295 First born 23 65 123 Yes
## 170 126 293 First born 29 59 110 <NA>
## 171 121 272 First born 22 62 109 Not
## 172 121 271 First born 25 68 118 Yes
## 173 138 287 First born 24 65 115 Not
## 174 136 278 First born 23 61 105 Not
## 175 120 279 First born 30 66 131 Not
## 176 122 278 First born 31 72 155 Yes
## 177 134 267 First born 30 66 170 Not
## 178 101 280 First born 25 65 123 Yes
## 179 112 288 First born 32 62 125 Not
## 180 132 290 First born 25 64 120 Not
## 181 136 285 First born 23 62 175 Not
## 182 113 277 First born 23 65 192 Yes
## 183 96 271 First born 23 64 116 Not
## 184 124 277 First born 29 63 220 Not
## 185 113 306 First born 21 62 150 Not
## 186 131 286 First born 34 NA NA Yes
## 187 137 258 First born 25 63 117 Not
## 188 133 268 First born 24 61 93 Not
## 189 107 244 First born 20 58 97 Not
## 190 96 265 First born 28 59 135 Yes
## 191 142 278 First born 35 66 136 Yes
## 192 136 275 First born 22 63 110 Not
## 193 75 239 First born 26 63 124 Yes
## 194 125 302 First born 32 61 NA Yes
## 195 104 295 First born 26 65 155 Yes
## 196 130 274 First born 30 63 150 Not
## 197 90 290 First born 22 63 168 Not
## 198 118 276 First born 22 66 147 Yes
## 199 123 320 First born 22 66 117 Not
## 200 137 291 First born 34 61 110 Not
## 201 101 268 First born 19 63 140 Not
## 202 142 275 First born 25 64 132 Not
## 203 98 282 First born 20 63 97 Yes
## 204 124 283 First born 23 63 112 Not
## 205 151 310 First born 21 65 NA Not
## 206 109 281 First born 23 61 105 Not
## 207 150 285 First born 22 61 110 Yes
## 208 119 282 First born 26 68 150 Yes
## 209 131 280 First born 38 65 125 Not
## 210 101 272 First born 29 63 150 Yes
## 211 113 246 First born 19 62 138 Yes
## 212 127 270 First born 25 62 150 Not
## 213 97 260 First born 23 61 99 Yes
## 214 117 282 First born 28 64 115 Not
## 215 150 290 First born 21 65 125 Not
## 216 85 234 First born 33 67 130 Not
## 217 128 288 First born 27 70 145 Not
## 218 105 233 First born 34 61 130 Not
## 219 90 269 First born 26 67 125 <NA>
## 220 115 274 First born 22 65 130 Yes
## 221 107 290 First born 28 62 135 Not
## 222 121 275 First born 24 63 121 Yes
## 223 119 286 First born 20 64 180 Not
## 224 117 275 First born 20 64 145 Yes
## 225 134 264 First born 26 68 136 Not
## 226 117 288 First born 35 65 142 Not
## 227 115 268 First born 28 66 128 Not
## 228 110 254 First born 23 63 120 Yes
## 229 130 282 First born 21 62 106 Yes
## 230 140 274 First born 23 63 106 Yes
## 231 111 284 First born 22 NA NA Yes
## 232 93 249 First born 33 66 117 Not
## 233 154 292 First born 42 65 116 Yes
## 234 125 290 First born 19 64 127 Not
## 235 93 318 First born 31 66 135 Not
## 236 122 277 First born 33 63 135 Yes
## 237 129 267 First born 22 63 160 Not
## 238 126 276 First born 23 63 120 Not
## 239 85 274 First born 24 68 155 Not
## 240 173 293 First born 30 63 110 Not
## 241 144 329 First born 22 65 190 Yes
## 242 114 278 First born 25 65 140 Yes
## 243 111 NA First born 27 63 105 Yes
## 244 154 287 First born 27 65 125 Yes
## 245 150 274 First born 25 67 117 Yes
## 246 111 278 First born 21 62 125 Not
## 247 126 277 First born 32 66 128 Not
## 248 122 261 First born 28 65 124 Not
## 249 141 282 First born 24 68 169 Not
## 250 142 274 First born 24 63 125 Not
## 251 99 262 First born 38 59 110 Yes
## 252 113 286 First born 23 63 105 Not
## 253 149 282 First born 21 61 110 Not
## 254 117 328 First born 29 65 125 Yes
## 255 130 274 First born 26 64 185 <NA>
## 256 106 275 First born 31 65 142 <NA>
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## 302 109 286 First born 24 64 125 Yes
## 303 111 306 First born 27 61 102 Not
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## 305 136 290 First born 26 66 135 Not
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## 872 125 283 First born 29 65 125 Not
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## 878 121 271 Unknown 34 63 129 Yes
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## 881 90 266 Unknown 26 67 135 Not
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## 885 123 282 First born 30 63 118 Not
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## 894 88 273 First born 20 66 110 Yes
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## 898 129 281 First born 31 67 155 Not
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## 900 85 255 First born 24 68 159 Not
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## 902 124 275 First born 28 61 116 Not
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## 907 116 291 First born 26 66 153 Not
## 908 127 272 First born 20 64 130 Yes
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## 913 58 245 First born 34 64 156 Yes
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## 915 110 277 Unknown 19 62 160 Not
## 916 129 278 First born 27 63 128 Not
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## 921 108 274 First born 28 66 175 <NA>
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## 923 139 281 First born 27 63 137 Not
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## 927 131 285 First born 26 64 130 Not
## 928 77 238 First born 38 67 135 Yes
## 929 124 283 Unknown 33 67 156 Yes
## 930 104 270 Unknown 26 62 115 Not
## 931 102 267 Unknown 24 61 109 Yes
## 932 94 268 First born 30 62 105 Yes
## 933 158 295 Unknown 37 70 137 Not
## 934 112 275 Unknown 21 68 143 Yes
## 935 119 286 First born 26 64 123 Yes
## 936 97 279 First born 29 68 178 Yes
## 937 99 252 First born 21 64 120 Not
## 938 115 264 Unknown 23 67 134 Yes
## 939 139 284 First born 37 61 121 Not
## 940 144 304 Unknown 27 58 102 Yes
## 941 99 270 First born 22 63 115 Yes
## 942 105 280 Unknown 22 63 116 Not
## 943 89 275 First born 34 66 170 Not
## 944 129 270 First born 43 67 160 Not
## 945 119 270 Unknown 20 64 109 Not
## 946 114 291 First born 35 60 112 Not
## 947 106 289 First born 28 67 120 Yes
## 948 122 292 Unknown 34 65 133 Not
## 949 136 261 First born 24 65 110 Not
## 950 121 286 Unknown 22 69 130 Yes
## 951 112 282 First born 26 65 122 Not
## 952 112 266 First born 26 64 122 Not
## 953 123 314 First born 22 61 121 Yes
## 954 139 286 First born 33 65 125 Yes
## 955 125 290 First born 36 59 105 Not
## 956 105 295 Unknown 20 64 112 Yes
## 957 130 276 First born 41 68 130 Not
## 958 146 294 First born 22 66 145 Yes
## 959 133 290 First born 21 64 145 Not
## 960 147 296 Unknown 19 67 124 Not
## 961 109 269 First born 23 63 113 Not
## 962 122 286 First born 23 64 120 Yes
## 963 135 260 First born 43 65 135 Not
## 964 107 NA First born 19 60 118 Not
## 965 117 272 First born 32 66 118 Not
## 966 138 284 First born 30 66 133 Yes
## 967 120 283 First born 28 64 122 Yes
## 968 119 273 First born 35 65 125 Yes
## 969 118 278 Unknown 19 62 126 Not
## 970 105 330 First born 23 64 112 Yes
## 971 113 306 Unknown 21 65 137 Not
## 972 136 NA First born 36 66 135 Not
## 973 148 291 Unknown 21 63 115 Not
## 974 140 281 Unknown 22 69 135 Not
## 975 134 287 Unknown 33 67 131 Not
## 976 120 280 First born 31 61 111 Not
## 977 123 296 Unknown 26 64 110 Yes
## 978 102 275 First born 43 64 160 Not
## 979 55 204 First born 35 65 140 Not
## 980 103 276 Unknown 19 63 149 Yes
## 981 123 283 First born 21 65 110 Not
## 982 105 270 Unknown 27 65 134 Yes
## 983 138 289 First born 33 65 155 Not
## 984 128 281 First born 28 63 150 Not
## 985 139 285 First born 30 65 129 Yes
## 986 104 288 Unknown 27 61 122 Yes
## 987 159 296 Unknown 27 64 112 Not
## 988 118 276 First born 29 62 130 Yes
## 989 99 285 First born 25 69 128 Yes
## 990 144 281 First born 20 63 120 Not
## 991 121 270 First born 25 62 108 Yes
## 992 117 265 Unknown 24 66 98 Not
## 993 119 293 Unknown 23 65 127 Not
## 994 105 281 Unknown 19 61 130 Not
## 995 125 283 First born 37 63 145 Yes
## 996 119 259 First born 37 62 130 Not
## 997 101 273 First born 39 60 113 Not
## 998 105 277 Unknown 25 64 156 Not
## 999 110 281 First born 27 60 110 Not
## 1000 100 270 Unknown 21 65 132 Yes
## 1001 98 284 First born 29 68 140 Not
## 1002 127 276 First born 37 64 159 Not
## 1003 117 324 First born 22 62 164 Yes
## 1004 122 278 First born 37 68 114 Not
## 1005 122 273 Unknown 23 64 130 Yes
## 1006 118 281 Unknown 36 66 140 Yes
## 1007 137 303 Unknown 23 66 127 Yes
## 1008 120 275 First born 32 63 115 Yes
## 1009 143 285 First born 27 68 185 Not
## 1010 108 270 First born 29 67 124 Yes
## 1011 131 284 Unknown 19 61 114 Yes
## 1012 110 277 First born 36 61 116 Not
## 1013 105 276 First born 20 62 112 Yes
## 1014 133 274 First born 30 63 NA Not
## 1015 125 255 First born 23 63 133 Not
## 1016 78 258 Unknown 24 66 115 Yes
## 1017 114 289 First born 36 60 115 Not
## 1018 111 278 First born 29 65 145 Yes
## 1019 103 250 First born 40 59 140 Not
## 1020 114 276 First born 26 62 127 Not
## 1021 75 247 First born 36 64 120 Yes
## 1022 169 296 First born 33 67 185 Not
## 1023 94 271 First born 36 61 130 Yes
## 1024 150 287 First born 36 62 135 Not
## 1025 144 248 First born 30 70 145 Not
## 1026 144 291 First born 28 67 130 Not
## 1027 143 313 First born 20 68 150 Not
## 1028 145 304 Unknown 25 63 109 Yes
## 1029 121 285 First born 34 64 110 Not
## 1030 105 256 First born 31 66 142 Not
## 1031 134 286 First born 25 64 125 Not
## 1032 129 294 Unknown 21 65 132 Not
## 1033 114 276 First born 24 63 110 Not
## 1034 97 265 First born 30 61 110 Not
## 1035 160 292 First born 28 64 120 Not
## 1036 65 237 First born 31 67 130 Not
## 1037 145 288 First born 28 64 116 Not
## 1038 95 273 First born 23 60 90 Not
## 1039 139 293 Unknown 21 69 130 Not
## 1040 123 288 First born 27 63 125 Not
## 1041 109 283 First born 23 65 112 Yes
## 1042 110 268 First born 34 64 127 Not
## 1043 122 296 Unknown 24 65 132 Not
## 1044 115 307 First born 34 65 128 Yes
## 1045 117 323 First born 26 62 NA Not
## 1046 108 279 Unknown 19 64 115 Not
## 1047 120 287 First born 23 67 116 Yes
## 1048 131 269 First born 36 68 145 Not
## 1049 136 283 Unknown 24 63 119 Not
## 1050 125 290 First born 32 63 135 Not
## 1051 96 285 Unknown 20 66 117 Yes
## 1052 102 282 Unknown 29 65 125 Yes
## 1053 102 288 Unknown 18 65 117 Not
## 1054 112 277 Unknown 22 67 120 Not
## 1055 135 272 First born 30 65 130 Not
## 1056 91 266 First born 23 60 120 Yes
## 1057 129 276 First born 31 63 125 Not
## 1058 155 290 First born 26 66 129 Yes
## 1059 109 274 First born 33 69 144 Yes
## 1060 80 262 Unknown 31 61 100 Yes
## 1061 125 273 First born 30 64 145 Not
## 1062 94 284 First born 24 63 104 Yes
## 1063 148 281 First born 27 63 110 Yes
## 1064 73 277 First born 29 65 145 Not
## 1065 123 267 Unknown 19 66 132 Yes
## 1066 65 232 First born 24 66 125 Yes
## 1067 118 279 Unknown 21 64 108 Not
## 1068 102 283 First born 39 60 119 Not
## 1069 120 280 First born 24 61 118 Not
## 1070 108 270 Unknown 21 65 130 Yes
## 1071 122 280 Unknown 45 62 128 Not
## 1072 103 268 First born 32 62 97 Yes
## 1073 105 312 First born 41 61 115 Yes
## 1074 126 273 Unknown 25 68 135 Not
## 1075 145 316 First born 22 67 142 Not
## 1076 139 293 First born 34 66 131 Not
## 1077 124 290 First born 26 65 165 Not
## 1078 121 282 First born 30 65 122 Not
## 1079 126 299 Unknown 21 60 114 Not
## 1080 119 286 Unknown 33 67 137 Not
## 1081 114 277 Unknown 19 63 107 Not
## 1082 118 272 First born 23 64 113 Not
## 1083 127 295 First born 36 65 145 Not
## 1084 117 290 Unknown 22 67 110 Not
## 1085 137 277 First born 41 65 126 Not
## 1086 133 292 First born 29 65 135 Not
## 1087 100 264 First born 28 60 111 Yes
## 1088 107 273 Unknown 26 65 135 Not
## 1089 115 276 Unknown 20 62 105 Yes
## 1090 91 292 Unknown 26 61 113 Yes
## 1091 112 287 First born 27 64 110 Yes
## 1092 125 289 Unknown 31 61 120 Not
## 1093 157 291 First born 33 65 121 Not
## 1094 108 256 Unknown 26 67 130 Not
## 1095 130 279 First born 31 62 122 Not
## 1096 135 289 First born 25 64 127 Not
## 1097 123 277 First born 24 66 122 Not
## 1098 100 281 First born 24 61 115 Not
## 1099 124 277 Unknown 23 64 104 Not
## 1100 174 284 First born 39 65 163 Not
## 1101 129 278 First born 26 67 146 Not
## 1102 119 275 First born 27 59 113 Yes
## 1103 126 272 Unknown 35 61 120 Yes
## 1104 128 267 First born 37 61 142 Not
## 1105 116 282 Unknown 19 64 124 Not
## 1106 100 285 First born 18 68 127 Yes
## 1107 96 285 First born 37 66 135 Yes
## 1108 131 279 Unknown 20 68 122 Yes
## 1109 110 292 First born 35 62 127 Not
## 1110 108 278 First born 28 63 125 Yes
## 1111 129 275 First born 24 65 135 Not
## 1112 141 285 First born 23 67 150 Not
## 1113 110 276 First born 31 70 155 Not
## 1114 118 273 First born 21 63 120 Not
## 1115 111 267 Unknown 24 60 115 Not
## 1116 160 297 First born 20 68 136 Not
## 1117 120 280 First born 30 60 115 Not
## 1118 121 281 First born 29 63 108 Not
## 1119 113 282 First born 30 64 118 Yes
## 1120 117 270 First born 23 58 115 Not
## 1121 158 267 First born 35 64 125 Not
## 1122 128 277 First born 39 61 120 Not
## 1123 158 289 First born 30 66 140 Not
## 1124 133 289 First born 22 65 123 Yes
## 1125 163 298 First born 37 61 98 Not
## 1126 128 282 Unknown 19 66 118 Not
## 1127 126 271 Unknown 21 60 105 Not
## 1128 127 283 First born 42 62 154 Yes
## 1129 134 287 First born 40 63 118 Not
## 1130 140 274 First born 41 63 122 Not
## 1131 102 285 First born 29 63 117 Yes
## 1132 100 252 First born 24 61 150 Not
## 1133 120 295 First born 29 59 100 Yes
## 1134 98 279 Unknown 18 65 115 Yes
## 1135 130 246 First born 19 62 118 Not
## 1136 104 280 First born 41 63 118 Yes
## 1137 122 285 First born 31 62 102 Yes
## 1138 137 276 Unknown 25 64 127 Not
## 1139 114 285 Unknown 20 61 104 Not
## 1140 63 236 Unknown 24 58 99 Not
## 1141 98 318 First born 23 63 107 Not
## 1142 99 268 First born 32 63 124 Yes
## 1143 89 238 Unknown 26 64 136 Not
## 1144 117 283 First born 22 65 142 Yes
## 1145 143 281 First born 29 67 132 Not
## 1146 106 279 First born 29 63 125 Yes
## 1147 99 246 First born 35 62 106 Not
## 1148 156 300 First born 27 65 120 Yes
## 1149 72 266 Unknown 25 66 200 Yes
## 1150 75 266 First born 37 61 113 Yes
## 1151 97 285 First born 35 61 112 Yes
## 1152 106 264 First born 41 64 114 Not
## 1153 91 225 First born 18 68 117 Yes
## 1154 117 269 Unknown 28 61 99 Not
## 1155 117 284 First born 25 66 177 Yes
## 1156 112 291 First born 23 66 145 Not
## 1157 112 270 First born 29 61 124 Not
## 1158 141 293 First born 28 61 125 Not
## 1159 131 259 First born 19 63 134 Not
## 1160 130 290 First born 19 65 123 Yes
## 1161 132 270 First born 26 67 140 Not
## 1162 114 265 First born 23 67 130 Yes
## 1163 160 291 First born 34 64 110 Yes
## 1164 106 283 First born 24 63 119 Not
## 1165 84 260 Unknown 20 64 104 Yes
## 1166 112 268 Unknown 25 59 103 Not
## 1167 139 311 First born 37 66 135 Not
## 1168 104 267 First born 30 63 180 Not
## 1169 130 294 First born 32 63 110 Yes
## 1170 71 254 First born 19 61 145 Yes
## 1171 82 270 First born 21 65 150 Yes
## 1172 119 280 Unknown 21 64 128 Not
## 1173 123 353 First born 26 63 115 Not
## 1174 115 278 First born 27 59 95 Not
## 1175 124 289 Unknown 21 67 145 Yes
## 1176 138 292 First born 25 65 130 Yes
## 1177 88 276 First born 25 63 103 Yes
## 1178 146 305 First born 23 NA NA Not
## 1179 128 241 Unknown 17 64 126 Not
## 1180 82 274 First born 31 64 101 Yes
## 1181 100 274 First born 24 63 113 Not
## 1182 114 271 First born 32 61 130 Not
## 1183 97 269 First born 20 65 137 Yes
## 1184 126 298 First born 24 61 112 Not
## 1185 122 275 Unknown 20 65 127 Not
## 1186 152 295 First born 39 62 140 Not
## 1187 116 274 First born 21 62 110 Yes
## 1188 132 302 First born 36 63 145 Yes
## 1189 84 260 Unknown 37 66 140 Not
## 1190 119 277 Unknown 18 61 89 Yes
## 1191 104 275 First born 24 NA NA Not
## 1192 106 312 First born 24 62 135 Yes
## 1193 124 NA Unknown 39 65 228 Not
## 1194 139 291 First born 24 65 160 Not
## 1195 103 273 First born 36 65 158 Yes
## 1196 112 299 First born 24 67 145 Yes
## 1197 96 276 First born 33 64 127 Yes
## 1198 102 281 Unknown 19 67 135 Yes
## 1199 120 300 First born 34 63 150 Yes
## 1200 102 338 First born 19 64 170 Not
## 1201 97 255 Unknown 22 63 107 Yes
## 1202 113 285 First born 22 70 145 Not
## 1203 130 297 First born 32 58 130 Not
## 1204 97 260 Unknown 25 63 115 Yes
## 1205 116 273 First born 31 61 120 Not
## 1206 114 266 First born 29 64 113 Not
## 1207 127 242 First born 17 61 135 Yes
## 1208 87 247 Unknown 18 66 125 Yes
## 1209 141 281 First born 29 54 156 Yes
## 1210 144 283 Unknown 25 66 140 Not
## 1211 116 273 First born 33 66 130 Yes
## 1212 75 265 First born 21 65 103 Yes
## 1213 138 286 Unknown 28 68 120 Not
## 1214 99 271 First born 39 69 151 Not
## 1215 118 293 First born 21 63 103 Not
## 1216 152 267 First born 28 NA 119 Yes
## 1217 97 266 First born 24 62 109 Not
## 1218 146 319 First born 28 66 145 Not
## 1219 81 285 First born 19 63 150 Yes
## 1220 110 321 First born 28 66 180 Not
## 1221 135 284 Unknown 19 60 95 Not
## 1222 114 290 Unknown 21 65 120 Yes
## 1223 124 288 Unknown 21 64 116 Yes
## 1224 115 262 Unknown 23 64 136 Yes
## 1225 143 281 First born 28 65 135 Yes
## 1226 113 287 Unknown 29 70 145 Yes
## 1227 109 244 Unknown 21 63 102 Yes
## 1228 103 278 First born 30 60 87 Yes
## 1229 118 276 First born 34 64 116 Not
## 1230 127 290 First born 27 65 121 Not
## 1231 132 270 First born 27 65 126 Not
## 1232 113 275 Unknown 27 60 100 Not
## 1233 128 265 First born 24 67 120 Not
## 1234 130 291 First born 30 65 150 Yes
## 1235 125 281 Unknown 21 65 110 Not
## 1236 117 297 First born 38 65 129 NotMedidad de Tendencia central
library(dplyr)
# Calcular la media, mediana y desviación estándar de la variable 'mpg'
mean(mtcars$mpg)## [1] 20.09062median(mtcars$mpg)## [1] 19.2sd(mtcars$mpg)## [1] 6.026948# Calcular la varianza y rango
var(mtcars$mpg)## [1] 36.3241range(mtcars$mpg)## [1] 10.4 33.9# Ejemplo
#probs es el rango en el que quiero calcular
mean(D.f$bwt)## [1] 119.5769median(D.f$bwt)## [1] 120mode(D.f$bwt)## [1] "numeric"var(D.f$bwt)## [1] 332.5682sd(D.f$bwt)## [1] 18.23645quantile(D.f$bwt,probs=c(0.25,0.40,0.90))## 25% 40% 90%
## 108.75 116.00 142.00#Sacar la media,mediana y demas cuando tienen datos NA
D.f%>%pull(bwt)%>%mean## [1] 119.5769D.f%>%pull(gestation)%>%median## [1] NAD.f$gestation[is.na(D.f$gestation)] <- median(D.f$gestation, na.rm = TRUE)
D.f## bwt gestation parity age height weight smoke
## 1 120 284 First born 27 62 100 Not
## 2 113 282 First born 33 64 135 Not
## 3 128 279 First born 28 64 115 Yes
## 4 123 280 First born 36 69 190 Not
## 5 108 282 First born 23 67 125 Yes
## 6 136 286 First born 25 62 93 Not
## 7 138 244 First born 33 62 178 Not
## 8 132 245 First born 23 65 140 Not
## 9 120 289 First born 25 62 125 Not
## 10 143 299 First born 30 66 136 Yes
## 11 140 351 First born 27 68 120 Not
## 12 144 282 First born 32 64 124 Yes
## 13 141 279 First born 23 63 128 Yes
## 14 110 281 First born 36 61 99 Yes
## 15 114 273 First born 30 63 154 Not
## 16 115 285 First born 38 63 130 Not
## 17 92 255 First born 25 65 125 Yes
## 18 115 261 First born 33 60 125 Yes
## 19 144 261 First born 33 68 170 Not
## 20 119 288 First born 43 66 142 Yes
## 21 105 270 First born 22 56 93 Not
## 22 115 274 First born 27 67 175 Yes
## 23 137 287 First born 25 66 145 Not
## 24 122 276 First born 30 68 182 Not
## 25 131 294 First born 23 65 122 Not
## 26 103 261 First born 27 65 112 Yes
## 27 146 280 First born 26 58 106 Not
## 28 114 266 First born 20 65 175 Yes
## 29 125 292 First born 32 65 125 Not
## 30 114 274 First born 28 66 132 Yes
## 31 122 270 First born 26 61 105 Not
## 32 93 278 First born 34 61 146 Not
## 33 130 268 First born 30 66 123 Not
## 34 119 275 First born 23 60 105 Not
## 35 113 281 First born 24 65 120 Not
## 36 134 283 First born 22 67 130 Not
## 37 107 279 First born 24 63 115 Not
## 38 134 288 First born 23 63 92 Yes
## 39 122 267 First born 27 65 101 Yes
## 40 128 282 First born 31 65 NA Not
## 41 129 293 First born 30 61 160 Not
## 42 110 278 First born 23 63 177 Not
## 43 138 302 First born 26 NA NA Yes
## 44 111 270 First born 27 61 119 Not
## 45 87 248 First born 37 65 130 Yes
## 46 143 274 First born 27 63 110 Yes
## 47 155 294 First born 32 66 150 Not
## 48 110 272 First born 25 60 90 Not
## 49 122 275 First born 26 66 147 Not
## 50 145 291 First born 26 63 119 Yes
## 51 115 258 First born 26 62 130 Not
## 52 108 283 First born 31 65 148 Yes
## 53 102 282 First born 28 61 110 Not
## 54 143 286 First born 31 64 126 Not
## 55 146 267 First born 30 67 132 Not
## 56 124 275 First born 22 60 130 Not
## 57 124 278 First born 26 70 145 Yes
## 58 145 257 First born 33 65 140 Not
## 59 106 273 First born 28 60 116 Not
## 60 75 232 First born 33 61 110 Not
## 61 107 273 First born 24 61 96 Not
## 62 124 288 First born 22 67 118 Not
## 63 122 280 First born 23 65 125 Yes
## 64 101 245 First born 23 63 130 Yes
## 65 128 283 First born 28 63 125 Yes
## 66 104 282 First born 36 65 115 Yes
## 67 97 246 First born 37 63 150 Not
## 68 137 274 First born 26 69 137 Yes
## 69 103 273 First born 31 63 170 Yes
## 70 142 276 First born 38 63 170 Not
## 71 130 289 First born 27 66 130 Not
## 72 156 292 First born 26 63 118 Not
## 73 133 284 First born 25 66 125 Yes
## 74 120 274 First born 24 62 120 Not
## 75 91 270 First born 24 60 149 Yes
## 76 127 274 First born 21 62 110 Not
## 77 153 286 First born 26 63 107 Yes
## 78 121 276 First born 39 63 130 Not
## 79 120 277 First born 27 63 126 Not
## 80 99 272 First born 27 62 103 Yes
## 81 149 293 First born 35 65 116 Not
## 82 129 280 First born 23 64 104 Not
## 83 139 292 First born 25 68 135 Not
## 84 114 274 First born 33 67 148 Yes
## 85 138 287 First born 30 66 145 Not
## 86 129 274 First born 29 71 NA Yes
## 87 138 294 First born 32 65 117 Not
## 88 131 296 First born 37 63 143 Not
## 89 125 305 First born 22 70 196 Yes
## 90 114 280 First born 24 67 113 Yes
## 91 128 281 First born 33 59 117 Not
## 92 134 268 First born 28 62 112 Not
## 93 114 271 First born 27 60 104 Not
## 94 92 280 First born 31 67 130 Not
## 95 85 278 First born 23 61 103 Yes
## 96 135 282 First born 22 64 100 Not
## 97 87 255 First born 28 61 100 Yes
## 98 125 302 First born 37 62 162 Not
## 99 128 280 First born 35 62 110 Not
## 100 105 254 First born 29 64 137 Not
## 101 120 279 First born 27 60 121 Yes
## 102 119 274 First born 33 64 120 Not
## 103 116 286 First born 24 61 NA Not
## 104 107 280 First born 36 65 117 Yes
## 105 119 273 First born 24 61 108 Yes
## 106 133 279 First born 37 66 140 Not
## 107 155 287 First born 33 66 143 Not
## 108 126 273 First born 22 65 150 Not
## 109 129 303 First born 27 64 125 Not
## 110 137 274 First born 29 65 154 Not
## 111 103 269 First born 26 65 NA Yes
## 112 125 302 First born 28 65 125 Not
## 113 91 255 First born 19 67 136 Yes
## 114 134 293 First born 21 65 NA Not
## 115 95 279 First born 22 66 145 Yes
## 116 118 276 First born 29 64 114 Not
## 117 141 278 First born 33 66 109 Yes
## 118 131 283 First born 25 67 215 Not
## 119 121 264 First born 32 66 145 Not
## 120 100 243 First born 39 65 170 Yes
## 121 131 288 First born 24 61 103 Not
## 122 118 284 First born 26 66 133 Not
## 123 152 288 First born 35 67 130 Not
## 124 121 284 First born 34 69 155 Not
## 125 117 276 First born 31 69 150 Not
## 126 115 283 First born 25 61 150 Yes
## 127 112 277 First born 23 65 110 Not
## 128 94 267 First born 30 62 120 Yes
## 129 109 272 First born 35 66 154 Not
## 130 132 225 First born 28 67 148 Not
## 131 117 278 First born 25 62 103 Not
## 132 101 266 First born 20 67 110 Yes
## 133 112 294 First born 25 64 125 Yes
## 134 128 283 First born 24 60 100 Not
## 135 128 279 First born 25 66 147 Yes
## 136 117 258 First born 31 64 120 Not
## 137 134 278 First born 24 69 135 Not
## 138 127 284 First born 28 65 145 Not
## 139 93 269 First born 21 65 104 Yes
## 140 122 275 First born 27 65 165 Not
## 141 100 265 First born 39 62 107 Yes
## 142 147 293 First born 32 65 123 Not
## 143 120 299 First born 25 65 110 Not
## 144 144 277 First born 30 63 127 Not
## 145 105 268 First born 32 61 115 Yes
## 146 136 276 First born 23 66 155 Not
## 147 102 262 First born 24 63 125 Not
## 148 160 300 First born 29 71 175 Yes
## 149 113 275 First born 24 68 140 Yes
## 150 126 282 First born 38 66 250 Not
## 151 126 271 First born 29 68 148 Not
## 152 115 278 First born 29 61 128 Not
## 153 127 336 First born 29 NA NA Not
## 154 119 284 First born 20 66 132 Not
## 155 129 280 First born 23 NA NA Yes
## 156 123 318 First born 21 64 152 Not
## 157 118 282 First born 22 68 135 Yes
## 158 133 287 First born 24 60 104 Yes
## 159 105 281 First born 39 61 NA Not
## 160 134 290 First born 22 60 121 Not
## 161 144 288 First born 21 67 111 Not
## 162 111 273 First born 43 62 138 Not
## 163 125 262 First born 36 66 190 Not
## 164 135 296 First born 30 63 123 Not
## 165 134 289 First born 22 63 125 Not
## 166 116 289 First born 22 65 160 Yes
## 167 129 291 First born 29 69 123 Not
## 168 113 301 First born 26 67 105 Yes
## 169 131 295 First born 23 65 123 Yes
## 170 126 293 First born 29 59 110 <NA>
## 171 121 272 First born 22 62 109 Not
## 172 121 271 First born 25 68 118 Yes
## 173 138 287 First born 24 65 115 Not
## 174 136 278 First born 23 61 105 Not
## 175 120 279 First born 30 66 131 Not
## 176 122 278 First born 31 72 155 Yes
## 177 134 267 First born 30 66 170 Not
## 178 101 280 First born 25 65 123 Yes
## 179 112 288 First born 32 62 125 Not
## 180 132 290 First born 25 64 120 Not
## 181 136 285 First born 23 62 175 Not
## 182 113 277 First born 23 65 192 Yes
## 183 96 271 First born 23 64 116 Not
## 184 124 277 First born 29 63 220 Not
## 185 113 306 First born 21 62 150 Not
## 186 131 286 First born 34 NA NA Yes
## 187 137 258 First born 25 63 117 Not
## 188 133 268 First born 24 61 93 Not
## 189 107 244 First born 20 58 97 Not
## 190 96 265 First born 28 59 135 Yes
## 191 142 278 First born 35 66 136 Yes
## 192 136 275 First born 22 63 110 Not
## 193 75 239 First born 26 63 124 Yes
## 194 125 302 First born 32 61 NA Yes
## 195 104 295 First born 26 65 155 Yes
## 196 130 274 First born 30 63 150 Not
## 197 90 290 First born 22 63 168 Not
## 198 118 276 First born 22 66 147 Yes
## 199 123 320 First born 22 66 117 Not
## 200 137 291 First born 34 61 110 Not
## 201 101 268 First born 19 63 140 Not
## 202 142 275 First born 25 64 132 Not
## 203 98 282 First born 20 63 97 Yes
## 204 124 283 First born 23 63 112 Not
## 205 151 310 First born 21 65 NA Not
## 206 109 281 First born 23 61 105 Not
## 207 150 285 First born 22 61 110 Yes
## 208 119 282 First born 26 68 150 Yes
## 209 131 280 First born 38 65 125 Not
## 210 101 272 First born 29 63 150 Yes
## 211 113 246 First born 19 62 138 Yes
## 212 127 270 First born 25 62 150 Not
## 213 97 260 First born 23 61 99 Yes
## 214 117 282 First born 28 64 115 Not
## 215 150 290 First born 21 65 125 Not
## 216 85 234 First born 33 67 130 Not
## 217 128 288 First born 27 70 145 Not
## 218 105 233 First born 34 61 130 Not
## 219 90 269 First born 26 67 125 <NA>
## 220 115 274 First born 22 65 130 Yes
## 221 107 290 First born 28 62 135 Not
## 222 121 275 First born 24 63 121 Yes
## 223 119 286 First born 20 64 180 Not
## 224 117 275 First born 20 64 145 Yes
## 225 134 264 First born 26 68 136 Not
## 226 117 288 First born 35 65 142 Not
## 227 115 268 First born 28 66 128 Not
## 228 110 254 First born 23 63 120 Yes
## 229 130 282 First born 21 62 106 Yes
## 230 140 274 First born 23 63 106 Yes
## 231 111 284 First born 22 NA NA Yes
## 232 93 249 First born 33 66 117 Not
## 233 154 292 First born 42 65 116 Yes
## 234 125 290 First born 19 64 127 Not
## 235 93 318 First born 31 66 135 Not
## 236 122 277 First born 33 63 135 Yes
## 237 129 267 First born 22 63 160 Not
## 238 126 276 First born 23 63 120 Not
## 239 85 274 First born 24 68 155 Not
## 240 173 293 First born 30 63 110 Not
## 241 144 329 First born 22 65 190 Yes
## 242 114 278 First born 25 65 140 Yes
## 243 111 280 First born 27 63 105 Yes
## 244 154 287 First born 27 65 125 Yes
## 245 150 274 First born 25 67 117 Yes
## 246 111 278 First born 21 62 125 Not
## 247 126 277 First born 32 66 128 Not
## 248 122 261 First born 28 65 124 Not
## 249 141 282 First born 24 68 169 Not
## 250 142 274 First born 24 63 125 Not
## 251 99 262 First born 38 59 110 Yes
## 252 113 286 First born 23 63 105 Not
## 253 149 282 First born 21 61 110 Not
## 254 117 328 First born 29 65 125 Yes
## 255 130 274 First born 26 64 185 <NA>
## 256 106 275 First born 31 65 142 <NA>
## 257 128 290 First born 22 64 118 Not
## 258 125 286 First born 21 64 139 Not
## 259 114 290 First born 30 66 160 Not
## 260 130 285 First born 23 63 128 Yes
## 261 116 148 First born 28 66 135 Not
## 262 81 256 First born 30 64 148 Yes
## 263 124 287 First born 27 62 105 Yes
## 264 125 292 First born 22 65 122 Not
## 265 110 262 First born 25 66 140 Not
## 266 125 279 First born 23 63 104 Yes
## 267 138 294 First born 40 64 125 Not
## 268 142 284 First born 39 66 132 Not
## 269 115 278 First born 23 60 102 Yes
## 270 102 280 First born 38 67 140 Not
## 271 140 294 First born 25 61 103 Not
## 272 133 276 Unknown 22 63 119 Not
## 273 127 290 First born 35 66 165 Not
## 274 104 274 Unknown 20 62 115 Yes
## 275 119 275 First born 42 67 156 Yes
## 276 152 301 First born 29 65 150 Not
## 277 123 284 Unknown 20 65 120 Yes
## 278 143 273 First born 19 66 135 Not
## 279 131 308 First born 40 65 160 Not
## 280 141 319 Unknown 20 67 140 Yes
## 281 129 277 First born 30 66 142 Yes
## 282 113 282 Unknown 36 59 140 Not
## 283 119 292 First born 33 62 118 Yes
## 284 109 295 Unknown 23 63 103 Yes
## 285 104 280 Unknown 27 68 146 Yes
## 286 131 282 Unknown 21 66 126 Not
## 287 110 293 Unknown 28 64 135 Yes
## 288 148 279 First born 27 71 189 Not
## 289 137 283 Unknown 20 65 157 Not
## 290 117 283 First born 27 63 108 Not
## 291 115 302 Unknown 22 67 135 Not
## 292 98 280 First born 35 64 122 Yes
## 293 136 303 Unknown 20 68 148 Yes
## 294 121 276 Unknown 23 71 152 Yes
## 295 132 285 Unknown 25 63 140 Not
## 296 91 264 First born 36 60 100 Yes
## 297 119 294 First born 34 59 105 Not
## 298 85 273 First born 26 60 105 Yes
## 299 106 271 Unknown 26 61 110 Yes
## 300 132 284 First born 29 64 122 Not
## 301 80 266 Unknown 25 62 125 Not
## 302 109 286 First born 24 64 125 Yes
## 303 111 306 First born 27 61 102 Not
## 304 143 292 Unknown 21 65 125 Not
## 305 136 290 First born 26 66 135 Not
## 306 110 285 Unknown 19 64 130 Not
## 307 98 257 First born 29 66 130 Yes
## 308 108 305 Unknown 24 65 112 Not
## 309 101 295 First born 18 62 145 Yes
## 310 71 281 First born 32 60 117 Yes
## 311 124 292 First born 29 68 176 Yes
## 312 93 256 First born 34 66 NA Yes
## 313 106 276 First born 30 66 130 Not
## 314 101 278 First born 25 62 112 Yes
## 315 100 277 First born 31 62 100 Yes
## 316 104 269 First born 35 63 110 Yes
## 317 117 270 First born 24 67 135 Yes
## 318 117 267 First born 29 65 120 Yes
## 319 149 279 First born 25 67 135 Not
## 320 135 284 First born 25 66 123 Not
## 321 110 283 Unknown 21 66 129 Not
## 322 121 276 First born 31 67 130 Not
## 323 142 285 Unknown 24 66 136 Not
## 324 104 260 First born 33 64 145 Not
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## 399 136 299 First born 29 64 115 Not
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## 401 121 282 First born 22 66 133 Not
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## 409 102 286 Unknown 22 64 140 Not
## 410 163 280 First born 35 69 139 Not
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## 451 120 269 Unknown 40 63 130 Not
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## 465 109 273 First born 37 65 138 Yes
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## 492 125 288 First born 22 63 128 Yes
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## 505 114 283 Unknown 15 64 117 Yes
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## 589 125 283 First born 22 65 119 Not
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## 771 104 289 First born 24 60 104 Yes
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## 798 127 288 First born 28 65 155 Not
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## 843 162 284 First born 27 64 126 Not
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## 852 134 297 First born 27 67 170 Yes
## 853 145 308 First born 35 64 110 Yes
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## 868 116 277 First born 41 64 124 Yes
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## 872 125 283 First born 29 65 125 Not
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## 885 123 282 First born 30 63 118 Not
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## 894 88 273 First born 20 66 110 Yes
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## 898 129 281 First born 31 67 155 Not
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## 900 85 255 First born 24 68 159 Not
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## 902 124 275 First born 28 61 116 Not
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## 907 116 291 First born 26 66 153 Not
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## 913 58 245 First born 34 64 156 Yes
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## 915 110 277 Unknown 19 62 160 Not
## 916 129 278 First born 27 63 128 Not
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## 921 108 274 First born 28 66 175 <NA>
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## 930 104 270 Unknown 26 62 115 Not
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## 932 94 268 First born 30 62 105 Yes
## 933 158 295 Unknown 37 70 137 Not
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## 935 119 286 First born 26 64 123 Yes
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## 937 99 252 First born 21 64 120 Not
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## 939 139 284 First born 37 61 121 Not
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## 941 99 270 First born 22 63 115 Yes
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## 943 89 275 First born 34 66 170 Not
## 944 129 270 First born 43 67 160 Not
## 945 119 270 Unknown 20 64 109 Not
## 946 114 291 First born 35 60 112 Not
## 947 106 289 First born 28 67 120 Yes
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## 951 112 282 First born 26 65 122 Not
## 952 112 266 First born 26 64 122 Not
## 953 123 314 First born 22 61 121 Yes
## 954 139 286 First born 33 65 125 Yes
## 955 125 290 First born 36 59 105 Not
## 956 105 295 Unknown 20 64 112 Yes
## 957 130 276 First born 41 68 130 Not
## 958 146 294 First born 22 66 145 Yes
## 959 133 290 First born 21 64 145 Not
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## 961 109 269 First born 23 63 113 Not
## 962 122 286 First born 23 64 120 Yes
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## 965 117 272 First born 32 66 118 Not
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## 970 105 330 First born 23 64 112 Yes
## 971 113 306 Unknown 21 65 137 Not
## 972 136 280 First born 36 66 135 Not
## 973 148 291 Unknown 21 63 115 Not
## 974 140 281 Unknown 22 69 135 Not
## 975 134 287 Unknown 33 67 131 Not
## 976 120 280 First born 31 61 111 Not
## 977 123 296 Unknown 26 64 110 Yes
## 978 102 275 First born 43 64 160 Not
## 979 55 204 First born 35 65 140 Not
## 980 103 276 Unknown 19 63 149 Yes
## 981 123 283 First born 21 65 110 Not
## 982 105 270 Unknown 27 65 134 Yes
## 983 138 289 First born 33 65 155 Not
## 984 128 281 First born 28 63 150 Not
## 985 139 285 First born 30 65 129 Yes
## 986 104 288 Unknown 27 61 122 Yes
## 987 159 296 Unknown 27 64 112 Not
## 988 118 276 First born 29 62 130 Yes
## 989 99 285 First born 25 69 128 Yes
## 990 144 281 First born 20 63 120 Not
## 991 121 270 First born 25 62 108 Yes
## 992 117 265 Unknown 24 66 98 Not
## 993 119 293 Unknown 23 65 127 Not
## 994 105 281 Unknown 19 61 130 Not
## 995 125 283 First born 37 63 145 Yes
## 996 119 259 First born 37 62 130 Not
## 997 101 273 First born 39 60 113 Not
## 998 105 277 Unknown 25 64 156 Not
## 999 110 281 First born 27 60 110 Not
## 1000 100 270 Unknown 21 65 132 Yes
## 1001 98 284 First born 29 68 140 Not
## 1002 127 276 First born 37 64 159 Not
## 1003 117 324 First born 22 62 164 Yes
## 1004 122 278 First born 37 68 114 Not
## 1005 122 273 Unknown 23 64 130 Yes
## 1006 118 281 Unknown 36 66 140 Yes
## 1007 137 303 Unknown 23 66 127 Yes
## 1008 120 275 First born 32 63 115 Yes
## 1009 143 285 First born 27 68 185 Not
## 1010 108 270 First born 29 67 124 Yes
## 1011 131 284 Unknown 19 61 114 Yes
## 1012 110 277 First born 36 61 116 Not
## 1013 105 276 First born 20 62 112 Yes
## 1014 133 274 First born 30 63 NA Not
## 1015 125 255 First born 23 63 133 Not
## 1016 78 258 Unknown 24 66 115 Yes
## 1017 114 289 First born 36 60 115 Not
## 1018 111 278 First born 29 65 145 Yes
## 1019 103 250 First born 40 59 140 Not
## 1020 114 276 First born 26 62 127 Not
## 1021 75 247 First born 36 64 120 Yes
## 1022 169 296 First born 33 67 185 Not
## 1023 94 271 First born 36 61 130 Yes
## 1024 150 287 First born 36 62 135 Not
## 1025 144 248 First born 30 70 145 Not
## 1026 144 291 First born 28 67 130 Not
## 1027 143 313 First born 20 68 150 Not
## 1028 145 304 Unknown 25 63 109 Yes
## 1029 121 285 First born 34 64 110 Not
## 1030 105 256 First born 31 66 142 Not
## 1031 134 286 First born 25 64 125 Not
## 1032 129 294 Unknown 21 65 132 Not
## 1033 114 276 First born 24 63 110 Not
## 1034 97 265 First born 30 61 110 Not
## 1035 160 292 First born 28 64 120 Not
## 1036 65 237 First born 31 67 130 Not
## 1037 145 288 First born 28 64 116 Not
## 1038 95 273 First born 23 60 90 Not
## 1039 139 293 Unknown 21 69 130 Not
## 1040 123 288 First born 27 63 125 Not
## 1041 109 283 First born 23 65 112 Yes
## 1042 110 268 First born 34 64 127 Not
## 1043 122 296 Unknown 24 65 132 Not
## 1044 115 307 First born 34 65 128 Yes
## 1045 117 323 First born 26 62 NA Not
## 1046 108 279 Unknown 19 64 115 Not
## 1047 120 287 First born 23 67 116 Yes
## 1048 131 269 First born 36 68 145 Not
## 1049 136 283 Unknown 24 63 119 Not
## 1050 125 290 First born 32 63 135 Not
## 1051 96 285 Unknown 20 66 117 Yes
## 1052 102 282 Unknown 29 65 125 Yes
## 1053 102 288 Unknown 18 65 117 Not
## 1054 112 277 Unknown 22 67 120 Not
## 1055 135 272 First born 30 65 130 Not
## 1056 91 266 First born 23 60 120 Yes
## 1057 129 276 First born 31 63 125 Not
## 1058 155 290 First born 26 66 129 Yes
## 1059 109 274 First born 33 69 144 Yes
## 1060 80 262 Unknown 31 61 100 Yes
## 1061 125 273 First born 30 64 145 Not
## 1062 94 284 First born 24 63 104 Yes
## 1063 148 281 First born 27 63 110 Yes
## 1064 73 277 First born 29 65 145 Not
## 1065 123 267 Unknown 19 66 132 Yes
## 1066 65 232 First born 24 66 125 Yes
## 1067 118 279 Unknown 21 64 108 Not
## 1068 102 283 First born 39 60 119 Not
## 1069 120 280 First born 24 61 118 Not
## 1070 108 270 Unknown 21 65 130 Yes
## 1071 122 280 Unknown 45 62 128 Not
## 1072 103 268 First born 32 62 97 Yes
## 1073 105 312 First born 41 61 115 Yes
## 1074 126 273 Unknown 25 68 135 Not
## 1075 145 316 First born 22 67 142 Not
## 1076 139 293 First born 34 66 131 Not
## 1077 124 290 First born 26 65 165 Not
## 1078 121 282 First born 30 65 122 Not
## 1079 126 299 Unknown 21 60 114 Not
## 1080 119 286 Unknown 33 67 137 Not
## 1081 114 277 Unknown 19 63 107 Not
## 1082 118 272 First born 23 64 113 Not
## 1083 127 295 First born 36 65 145 Not
## 1084 117 290 Unknown 22 67 110 Not
## 1085 137 277 First born 41 65 126 Not
## 1086 133 292 First born 29 65 135 Not
## 1087 100 264 First born 28 60 111 Yes
## 1088 107 273 Unknown 26 65 135 Not
## 1089 115 276 Unknown 20 62 105 Yes
## 1090 91 292 Unknown 26 61 113 Yes
## 1091 112 287 First born 27 64 110 Yes
## 1092 125 289 Unknown 31 61 120 Not
## 1093 157 291 First born 33 65 121 Not
## 1094 108 256 Unknown 26 67 130 Not
## 1095 130 279 First born 31 62 122 Not
## 1096 135 289 First born 25 64 127 Not
## 1097 123 277 First born 24 66 122 Not
## 1098 100 281 First born 24 61 115 Not
## 1099 124 277 Unknown 23 64 104 Not
## 1100 174 284 First born 39 65 163 Not
## 1101 129 278 First born 26 67 146 Not
## 1102 119 275 First born 27 59 113 Yes
## 1103 126 272 Unknown 35 61 120 Yes
## 1104 128 267 First born 37 61 142 Not
## 1105 116 282 Unknown 19 64 124 Not
## 1106 100 285 First born 18 68 127 Yes
## 1107 96 285 First born 37 66 135 Yes
## 1108 131 279 Unknown 20 68 122 Yes
## 1109 110 292 First born 35 62 127 Not
## 1110 108 278 First born 28 63 125 Yes
## 1111 129 275 First born 24 65 135 Not
## 1112 141 285 First born 23 67 150 Not
## 1113 110 276 First born 31 70 155 Not
## 1114 118 273 First born 21 63 120 Not
## 1115 111 267 Unknown 24 60 115 Not
## 1116 160 297 First born 20 68 136 Not
## 1117 120 280 First born 30 60 115 Not
## 1118 121 281 First born 29 63 108 Not
## 1119 113 282 First born 30 64 118 Yes
## 1120 117 270 First born 23 58 115 Not
## 1121 158 267 First born 35 64 125 Not
## 1122 128 277 First born 39 61 120 Not
## 1123 158 289 First born 30 66 140 Not
## 1124 133 289 First born 22 65 123 Yes
## 1125 163 298 First born 37 61 98 Not
## 1126 128 282 Unknown 19 66 118 Not
## 1127 126 271 Unknown 21 60 105 Not
## 1128 127 283 First born 42 62 154 Yes
## 1129 134 287 First born 40 63 118 Not
## 1130 140 274 First born 41 63 122 Not
## 1131 102 285 First born 29 63 117 Yes
## 1132 100 252 First born 24 61 150 Not
## 1133 120 295 First born 29 59 100 Yes
## 1134 98 279 Unknown 18 65 115 Yes
## 1135 130 246 First born 19 62 118 Not
## 1136 104 280 First born 41 63 118 Yes
## 1137 122 285 First born 31 62 102 Yes
## 1138 137 276 Unknown 25 64 127 Not
## 1139 114 285 Unknown 20 61 104 Not
## 1140 63 236 Unknown 24 58 99 Not
## 1141 98 318 First born 23 63 107 Not
## 1142 99 268 First born 32 63 124 Yes
## 1143 89 238 Unknown 26 64 136 Not
## 1144 117 283 First born 22 65 142 Yes
## 1145 143 281 First born 29 67 132 Not
## 1146 106 279 First born 29 63 125 Yes
## 1147 99 246 First born 35 62 106 Not
## 1148 156 300 First born 27 65 120 Yes
## 1149 72 266 Unknown 25 66 200 Yes
## 1150 75 266 First born 37 61 113 Yes
## 1151 97 285 First born 35 61 112 Yes
## 1152 106 264 First born 41 64 114 Not
## 1153 91 225 First born 18 68 117 Yes
## 1154 117 269 Unknown 28 61 99 Not
## 1155 117 284 First born 25 66 177 Yes
## 1156 112 291 First born 23 66 145 Not
## 1157 112 270 First born 29 61 124 Not
## 1158 141 293 First born 28 61 125 Not
## 1159 131 259 First born 19 63 134 Not
## 1160 130 290 First born 19 65 123 Yes
## 1161 132 270 First born 26 67 140 Not
## 1162 114 265 First born 23 67 130 Yes
## 1163 160 291 First born 34 64 110 Yes
## 1164 106 283 First born 24 63 119 Not
## 1165 84 260 Unknown 20 64 104 Yes
## 1166 112 268 Unknown 25 59 103 Not
## 1167 139 311 First born 37 66 135 Not
## 1168 104 267 First born 30 63 180 Not
## 1169 130 294 First born 32 63 110 Yes
## 1170 71 254 First born 19 61 145 Yes
## 1171 82 270 First born 21 65 150 Yes
## 1172 119 280 Unknown 21 64 128 Not
## 1173 123 353 First born 26 63 115 Not
## 1174 115 278 First born 27 59 95 Not
## 1175 124 289 Unknown 21 67 145 Yes
## 1176 138 292 First born 25 65 130 Yes
## 1177 88 276 First born 25 63 103 Yes
## 1178 146 305 First born 23 NA NA Not
## 1179 128 241 Unknown 17 64 126 Not
## 1180 82 274 First born 31 64 101 Yes
## 1181 100 274 First born 24 63 113 Not
## 1182 114 271 First born 32 61 130 Not
## 1183 97 269 First born 20 65 137 Yes
## 1184 126 298 First born 24 61 112 Not
## 1185 122 275 Unknown 20 65 127 Not
## 1186 152 295 First born 39 62 140 Not
## 1187 116 274 First born 21 62 110 Yes
## 1188 132 302 First born 36 63 145 Yes
## 1189 84 260 Unknown 37 66 140 Not
## 1190 119 277 Unknown 18 61 89 Yes
## 1191 104 275 First born 24 NA NA Not
## 1192 106 312 First born 24 62 135 Yes
## 1193 124 280 Unknown 39 65 228 Not
## 1194 139 291 First born 24 65 160 Not
## 1195 103 273 First born 36 65 158 Yes
## 1196 112 299 First born 24 67 145 Yes
## 1197 96 276 First born 33 64 127 Yes
## 1198 102 281 Unknown 19 67 135 Yes
## 1199 120 300 First born 34 63 150 Yes
## 1200 102 338 First born 19 64 170 Not
## 1201 97 255 Unknown 22 63 107 Yes
## 1202 113 285 First born 22 70 145 Not
## 1203 130 297 First born 32 58 130 Not
## 1204 97 260 Unknown 25 63 115 Yes
## 1205 116 273 First born 31 61 120 Not
## 1206 114 266 First born 29 64 113 Not
## 1207 127 242 First born 17 61 135 Yes
## 1208 87 247 Unknown 18 66 125 Yes
## 1209 141 281 First born 29 54 156 Yes
## 1210 144 283 Unknown 25 66 140 Not
## 1211 116 273 First born 33 66 130 Yes
## 1212 75 265 First born 21 65 103 Yes
## 1213 138 286 Unknown 28 68 120 Not
## 1214 99 271 First born 39 69 151 Not
## 1215 118 293 First born 21 63 103 Not
## 1216 152 267 First born 28 NA 119 Yes
## 1217 97 266 First born 24 62 109 Not
## 1218 146 319 First born 28 66 145 Not
## 1219 81 285 First born 19 63 150 Yes
## 1220 110 321 First born 28 66 180 Not
## 1221 135 284 Unknown 19 60 95 Not
## 1222 114 290 Unknown 21 65 120 Yes
## 1223 124 288 Unknown 21 64 116 Yes
## 1224 115 262 Unknown 23 64 136 Yes
## 1225 143 281 First born 28 65 135 Yes
## 1226 113 287 Unknown 29 70 145 Yes
## 1227 109 244 Unknown 21 63 102 Yes
## 1228 103 278 First born 30 60 87 Yes
## 1229 118 276 First born 34 64 116 Not
## 1230 127 290 First born 27 65 121 Not
## 1231 132 270 First born 27 65 126 Not
## 1232 113 275 Unknown 27 60 100 Not
## 1233 128 265 First born 24 67 120 Not
## 1234 130 291 First born 30 65 150 Yes
## 1235 125 281 Unknown 21 65 110 Not
## 1236 117 297 First born 38 65 129 Notmean(D.f$age)## [1] NAD.f$age[is.na(D.f$age)] <- mean(D.f$age, na.rm = TRUE)
D.f## bwt gestation parity age height weight smoke
## 1 120 284 First born 27.00000 62 100 Not
## 2 113 282 First born 33.00000 64 135 Not
## 3 128 279 First born 28.00000 64 115 Yes
## 4 123 280 First born 36.00000 69 190 Not
## 5 108 282 First born 23.00000 67 125 Yes
## 6 136 286 First born 25.00000 62 93 Not
## 7 138 244 First born 33.00000 62 178 Not
## 8 132 245 First born 23.00000 65 140 Not
## 9 120 289 First born 25.00000 62 125 Not
## 10 143 299 First born 30.00000 66 136 Yes
## 11 140 351 First born 27.00000 68 120 Not
## 12 144 282 First born 32.00000 64 124 Yes
## 13 141 279 First born 23.00000 63 128 Yes
## 14 110 281 First born 36.00000 61 99 Yes
## 15 114 273 First born 30.00000 63 154 Not
## 16 115 285 First born 38.00000 63 130 Not
## 17 92 255 First born 25.00000 65 125 Yes
## 18 115 261 First born 33.00000 60 125 Yes
## 19 144 261 First born 33.00000 68 170 Not
## 20 119 288 First born 43.00000 66 142 Yes
## 21 105 270 First born 22.00000 56 93 Not
## 22 115 274 First born 27.00000 67 175 Yes
## 23 137 287 First born 25.00000 66 145 Not
## 24 122 276 First born 30.00000 68 182 Not
## 25 131 294 First born 23.00000 65 122 Not
## 26 103 261 First born 27.00000 65 112 Yes
## 27 146 280 First born 26.00000 58 106 Not
## 28 114 266 First born 20.00000 65 175 Yes
## 29 125 292 First born 32.00000 65 125 Not
## 30 114 274 First born 28.00000 66 132 Yes
## 31 122 270 First born 26.00000 61 105 Not
## 32 93 278 First born 34.00000 61 146 Not
## 33 130 268 First born 30.00000 66 123 Not
## 34 119 275 First born 23.00000 60 105 Not
## 35 113 281 First born 24.00000 65 120 Not
## 36 134 283 First born 22.00000 67 130 Not
## 37 107 279 First born 24.00000 63 115 Not
## 38 134 288 First born 23.00000 63 92 Yes
## 39 122 267 First born 27.00000 65 101 Yes
## 40 128 282 First born 31.00000 65 NA Not
## 41 129 293 First born 30.00000 61 160 Not
## 42 110 278 First born 23.00000 63 177 Not
## 43 138 302 First born 26.00000 NA NA Yes
## 44 111 270 First born 27.00000 61 119 Not
## 45 87 248 First born 37.00000 65 130 Yes
## 46 143 274 First born 27.00000 63 110 Yes
## 47 155 294 First born 32.00000 66 150 Not
## 48 110 272 First born 25.00000 60 90 Not
## 49 122 275 First born 26.00000 66 147 Not
## 50 145 291 First born 26.00000 63 119 Yes
## 51 115 258 First born 26.00000 62 130 Not
## 52 108 283 First born 31.00000 65 148 Yes
## 53 102 282 First born 28.00000 61 110 Not
## 54 143 286 First born 31.00000 64 126 Not
## 55 146 267 First born 30.00000 67 132 Not
## 56 124 275 First born 22.00000 60 130 Not
## 57 124 278 First born 26.00000 70 145 Yes
## 58 145 257 First born 33.00000 65 140 Not
## 59 106 273 First born 28.00000 60 116 Not
## 60 75 232 First born 33.00000 61 110 Not
## 61 107 273 First born 24.00000 61 96 Not
## 62 124 288 First born 22.00000 67 118 Not
## 63 122 280 First born 23.00000 65 125 Yes
## 64 101 245 First born 23.00000 63 130 Yes
## 65 128 283 First born 28.00000 63 125 Yes
## 66 104 282 First born 36.00000 65 115 Yes
## 67 97 246 First born 37.00000 63 150 Not
## 68 137 274 First born 26.00000 69 137 Yes
## 69 103 273 First born 31.00000 63 170 Yes
## 70 142 276 First born 38.00000 63 170 Not
## 71 130 289 First born 27.00000 66 130 Not
## 72 156 292 First born 26.00000 63 118 Not
## 73 133 284 First born 25.00000 66 125 Yes
## 74 120 274 First born 24.00000 62 120 Not
## 75 91 270 First born 24.00000 60 149 Yes
## 76 127 274 First born 21.00000 62 110 Not
## 77 153 286 First born 26.00000 63 107 Yes
## 78 121 276 First born 39.00000 63 130 Not
## 79 120 277 First born 27.00000 63 126 Not
## 80 99 272 First born 27.00000 62 103 Yes
## 81 149 293 First born 35.00000 65 116 Not
## 82 129 280 First born 23.00000 64 104 Not
## 83 139 292 First born 25.00000 68 135 Not
## 84 114 274 First born 33.00000 67 148 Yes
## 85 138 287 First born 30.00000 66 145 Not
## 86 129 274 First born 29.00000 71 NA Yes
## 87 138 294 First born 32.00000 65 117 Not
## 88 131 296 First born 37.00000 63 143 Not
## 89 125 305 First born 22.00000 70 196 Yes
## 90 114 280 First born 24.00000 67 113 Yes
## 91 128 281 First born 33.00000 59 117 Not
## 92 134 268 First born 28.00000 62 112 Not
## 93 114 271 First born 27.00000 60 104 Not
## 94 92 280 First born 31.00000 67 130 Not
## 95 85 278 First born 23.00000 61 103 Yes
## 96 135 282 First born 22.00000 64 100 Not
## 97 87 255 First born 28.00000 61 100 Yes
## 98 125 302 First born 37.00000 62 162 Not
## 99 128 280 First born 35.00000 62 110 Not
## 100 105 254 First born 29.00000 64 137 Not
## 101 120 279 First born 27.00000 60 121 Yes
## 102 119 274 First born 33.00000 64 120 Not
## 103 116 286 First born 24.00000 61 NA Not
## 104 107 280 First born 36.00000 65 117 Yes
## 105 119 273 First born 24.00000 61 108 Yes
## 106 133 279 First born 37.00000 66 140 Not
## 107 155 287 First born 33.00000 66 143 Not
## 108 126 273 First born 22.00000 65 150 Not
## 109 129 303 First born 27.00000 64 125 Not
## 110 137 274 First born 29.00000 65 154 Not
## 111 103 269 First born 26.00000 65 NA Yes
## 112 125 302 First born 28.00000 65 125 Not
## 113 91 255 First born 19.00000 67 136 Yes
## 114 134 293 First born 21.00000 65 NA Not
## 115 95 279 First born 22.00000 66 145 Yes
## 116 118 276 First born 29.00000 64 114 Not
## 117 141 278 First born 33.00000 66 109 Yes
## 118 131 283 First born 25.00000 67 215 Not
## 119 121 264 First born 32.00000 66 145 Not
## 120 100 243 First born 39.00000 65 170 Yes
## 121 131 288 First born 24.00000 61 103 Not
## 122 118 284 First born 26.00000 66 133 Not
## 123 152 288 First born 35.00000 67 130 Not
## 124 121 284 First born 34.00000 69 155 Not
## 125 117 276 First born 31.00000 69 150 Not
## 126 115 283 First born 25.00000 61 150 Yes
## 127 112 277 First born 23.00000 65 110 Not
## 128 94 267 First born 30.00000 62 120 Yes
## 129 109 272 First born 35.00000 66 154 Not
## 130 132 225 First born 28.00000 67 148 Not
## 131 117 278 First born 25.00000 62 103 Not
## 132 101 266 First born 20.00000 67 110 Yes
## 133 112 294 First born 25.00000 64 125 Yes
## 134 128 283 First born 24.00000 60 100 Not
## 135 128 279 First born 25.00000 66 147 Yes
## 136 117 258 First born 31.00000 64 120 Not
## 137 134 278 First born 24.00000 69 135 Not
## 138 127 284 First born 28.00000 65 145 Not
## 139 93 269 First born 21.00000 65 104 Yes
## 140 122 275 First born 27.00000 65 165 Not
## 141 100 265 First born 39.00000 62 107 Yes
## 142 147 293 First born 32.00000 65 123 Not
## 143 120 299 First born 25.00000 65 110 Not
## 144 144 277 First born 30.00000 63 127 Not
## 145 105 268 First born 32.00000 61 115 Yes
## 146 136 276 First born 23.00000 66 155 Not
## 147 102 262 First born 24.00000 63 125 Not
## 148 160 300 First born 29.00000 71 175 Yes
## 149 113 275 First born 24.00000 68 140 Yes
## 150 126 282 First born 38.00000 66 250 Not
## 151 126 271 First born 29.00000 68 148 Not
## 152 115 278 First born 29.00000 61 128 Not
## 153 127 336 First born 29.00000 NA NA Not
## 154 119 284 First born 20.00000 66 132 Not
## 155 129 280 First born 23.00000 NA NA Yes
## 156 123 318 First born 21.00000 64 152 Not
## 157 118 282 First born 22.00000 68 135 Yes
## 158 133 287 First born 24.00000 60 104 Yes
## 159 105 281 First born 39.00000 61 NA Not
## 160 134 290 First born 22.00000 60 121 Not
## 161 144 288 First born 21.00000 67 111 Not
## 162 111 273 First born 43.00000 62 138 Not
## 163 125 262 First born 36.00000 66 190 Not
## 164 135 296 First born 30.00000 63 123 Not
## 165 134 289 First born 22.00000 63 125 Not
## 166 116 289 First born 22.00000 65 160 Yes
## 167 129 291 First born 29.00000 69 123 Not
## 168 113 301 First born 26.00000 67 105 Yes
## 169 131 295 First born 23.00000 65 123 Yes
## 170 126 293 First born 29.00000 59 110 <NA>
## 171 121 272 First born 22.00000 62 109 Not
## 172 121 271 First born 25.00000 68 118 Yes
## 173 138 287 First born 24.00000 65 115 Not
## 174 136 278 First born 23.00000 61 105 Not
## 175 120 279 First born 30.00000 66 131 Not
## 176 122 278 First born 31.00000 72 155 Yes
## 177 134 267 First born 30.00000 66 170 Not
## 178 101 280 First born 25.00000 65 123 Yes
## 179 112 288 First born 32.00000 62 125 Not
## 180 132 290 First born 25.00000 64 120 Not
## 181 136 285 First born 23.00000 62 175 Not
## 182 113 277 First born 23.00000 65 192 Yes
## 183 96 271 First born 23.00000 64 116 Not
## 184 124 277 First born 29.00000 63 220 Not
## 185 113 306 First born 21.00000 62 150 Not
## 186 131 286 First born 34.00000 NA NA Yes
## 187 137 258 First born 25.00000 63 117 Not
## 188 133 268 First born 24.00000 61 93 Not
## 189 107 244 First born 20.00000 58 97 Not
## 190 96 265 First born 28.00000 59 135 Yes
## 191 142 278 First born 35.00000 66 136 Yes
## 192 136 275 First born 22.00000 63 110 Not
## 193 75 239 First born 26.00000 63 124 Yes
## 194 125 302 First born 32.00000 61 NA Yes
## 195 104 295 First born 26.00000 65 155 Yes
## 196 130 274 First born 30.00000 63 150 Not
## 197 90 290 First born 22.00000 63 168 Not
## 198 118 276 First born 22.00000 66 147 Yes
## 199 123 320 First born 22.00000 66 117 Not
## 200 137 291 First born 34.00000 61 110 Not
## 201 101 268 First born 19.00000 63 140 Not
## 202 142 275 First born 25.00000 64 132 Not
## 203 98 282 First born 20.00000 63 97 Yes
## 204 124 283 First born 23.00000 63 112 Not
## 205 151 310 First born 21.00000 65 NA Not
## 206 109 281 First born 23.00000 61 105 Not
## 207 150 285 First born 22.00000 61 110 Yes
## 208 119 282 First born 26.00000 68 150 Yes
## 209 131 280 First born 38.00000 65 125 Not
## 210 101 272 First born 29.00000 63 150 Yes
## 211 113 246 First born 19.00000 62 138 Yes
## 212 127 270 First born 25.00000 62 150 Not
## 213 97 260 First born 23.00000 61 99 Yes
## 214 117 282 First born 28.00000 64 115 Not
## 215 150 290 First born 21.00000 65 125 Not
## 216 85 234 First born 33.00000 67 130 Not
## 217 128 288 First born 27.00000 70 145 Not
## 218 105 233 First born 34.00000 61 130 Not
## 219 90 269 First born 26.00000 67 125 <NA>
## 220 115 274 First born 22.00000 65 130 Yes
## 221 107 290 First born 28.00000 62 135 Not
## 222 121 275 First born 24.00000 63 121 Yes
## 223 119 286 First born 20.00000 64 180 Not
## 224 117 275 First born 20.00000 64 145 Yes
## 225 134 264 First born 26.00000 68 136 Not
## 226 117 288 First born 35.00000 65 142 Not
## 227 115 268 First born 28.00000 66 128 Not
## 228 110 254 First born 23.00000 63 120 Yes
## 229 130 282 First born 21.00000 62 106 Yes
## 230 140 274 First born 23.00000 63 106 Yes
## 231 111 284 First born 22.00000 NA NA Yes
## 232 93 249 First born 33.00000 66 117 Not
## 233 154 292 First born 42.00000 65 116 Yes
## 234 125 290 First born 19.00000 64 127 Not
## 235 93 318 First born 31.00000 66 135 Not
## 236 122 277 First born 33.00000 63 135 Yes
## 237 129 267 First born 22.00000 63 160 Not
## 238 126 276 First born 23.00000 63 120 Not
## 239 85 274 First born 24.00000 68 155 Not
## 240 173 293 First born 30.00000 63 110 Not
## 241 144 329 First born 22.00000 65 190 Yes
## 242 114 278 First born 25.00000 65 140 Yes
## 243 111 280 First born 27.00000 63 105 Yes
## 244 154 287 First born 27.00000 65 125 Yes
## 245 150 274 First born 25.00000 67 117 Yes
## 246 111 278 First born 21.00000 62 125 Not
## 247 126 277 First born 32.00000 66 128 Not
## 248 122 261 First born 28.00000 65 124 Not
## 249 141 282 First born 24.00000 68 169 Not
## 250 142 274 First born 24.00000 63 125 Not
## 251 99 262 First born 38.00000 59 110 Yes
## 252 113 286 First born 23.00000 63 105 Not
## 253 149 282 First born 21.00000 61 110 Not
## 254 117 328 First born 29.00000 65 125 Yes
## 255 130 274 First born 26.00000 64 185 <NA>
## 256 106 275 First born 31.00000 65 142 <NA>
## 257 128 290 First born 22.00000 64 118 Not
## 258 125 286 First born 21.00000 64 139 Not
## 259 114 290 First born 30.00000 66 160 Not
## 260 130 285 First born 23.00000 63 128 Yes
## 261 116 148 First born 28.00000 66 135 Not
## 262 81 256 First born 30.00000 64 148 Yes
## 263 124 287 First born 27.00000 62 105 Yes
## 264 125 292 First born 22.00000 65 122 Not
## 265 110 262 First born 25.00000 66 140 Not
## 266 125 279 First born 23.00000 63 104 Yes
## 267 138 294 First born 40.00000 64 125 Not
## 268 142 284 First born 39.00000 66 132 Not
## 269 115 278 First born 23.00000 60 102 Yes
## 270 102 280 First born 38.00000 67 140 Not
## 271 140 294 First born 25.00000 61 103 Not
## 272 133 276 Unknown 22.00000 63 119 Not
## 273 127 290 First born 35.00000 66 165 Not
## 274 104 274 Unknown 20.00000 62 115 Yes
## 275 119 275 First born 42.00000 67 156 Yes
## 276 152 301 First born 29.00000 65 150 Not
## 277 123 284 Unknown 20.00000 65 120 Yes
## 278 143 273 First born 19.00000 66 135 Not
## 279 131 308 First born 40.00000 65 160 Not
## 280 141 319 Unknown 20.00000 67 140 Yes
## 281 129 277 First born 30.00000 66 142 Yes
## 282 113 282 Unknown 36.00000 59 140 Not
## 283 119 292 First born 33.00000 62 118 Yes
## 284 109 295 Unknown 23.00000 63 103 Yes
## 285 104 280 Unknown 27.00000 68 146 Yes
## 286 131 282 Unknown 21.00000 66 126 Not
## 287 110 293 Unknown 28.00000 64 135 Yes
## 288 148 279 First born 27.00000 71 189 Not
## 289 137 283 Unknown 20.00000 65 157 Not
## 290 117 283 First born 27.00000 63 108 Not
## 291 115 302 Unknown 22.00000 67 135 Not
## 292 98 280 First born 35.00000 64 122 Yes
## 293 136 303 Unknown 20.00000 68 148 Yes
## 294 121 276 Unknown 23.00000 71 152 Yes
## 295 132 285 Unknown 25.00000 63 140 Not
## 296 91 264 First born 36.00000 60 100 Yes
## 297 119 294 First born 34.00000 59 105 Not
## 298 85 273 First born 26.00000 60 105 Yes
## 299 106 271 Unknown 26.00000 61 110 Yes
## 300 132 284 First born 29.00000 64 122 Not
## 301 80 266 Unknown 25.00000 62 125 Not
## 302 109 286 First born 24.00000 64 125 Yes
## 303 111 306 First born 27.00000 61 102 Not
## 304 143 292 Unknown 21.00000 65 125 Not
## 305 136 290 First born 26.00000 66 135 Not
## 306 110 285 Unknown 19.00000 64 130 Not
## 307 98 257 First born 29.00000 66 130 Yes
## 308 108 305 Unknown 24.00000 65 112 Not
## 309 101 295 First born 18.00000 62 145 Yes
## 310 71 281 First born 32.00000 60 117 Yes
## 311 124 292 First born 29.00000 68 176 Yes
## 312 93 256 First born 34.00000 66 NA Yes
## 313 106 276 First born 30.00000 66 130 Not
## 314 101 278 First born 25.00000 62 112 Yes
## 315 100 277 First born 31.00000 62 100 Yes
## 316 104 269 First born 35.00000 63 110 Yes
## 317 117 270 First born 24.00000 67 135 Yes
## 318 117 267 First born 29.00000 65 120 Yes
## 319 149 279 First born 25.00000 67 135 Not
## 320 135 284 First born 25.00000 66 123 Not
## 321 110 283 Unknown 21.00000 66 129 Not
## 322 121 276 First born 31.00000 67 130 Not
## 323 142 285 Unknown 24.00000 66 136 Not
## 324 104 260 First born 33.00000 64 145 Not
## 325 138 296 First born 34.00000 66 120 Not
## 326 112 278 Unknown 21.00000 63 120 Not
## 327 117 293 First born 39.00000 60 120 Yes
## 328 109 282 First born 25.00000 62 106 Yes
## 329 131 266 Unknown 28.00000 67 135 Not
## 330 120 273 First born 29.00000 64 130 Yes
## 331 116 270 First born 29.00000 63 132 Not
## 332 140 290 First born 23.00000 65 110 Not
## 333 103 273 Unknown 22.00000 64 110 Yes
## 334 120 279 Unknown 23.00000 67 135 Not
## 335 139 260 Unknown 32.00000 64 127 Not
## 336 123 254 First born 26.00000 62 130 Yes
## 337 104 280 Unknown 23.00000 64 107 Yes
## 338 131 283 First born 31.00000 NA NA Not
## 339 111 270 First born 22.00000 59 103 Not
## 340 122 277 First born 32.00000 63 157 Yes
## 341 116 271 Unknown 30.00000 67 144 Yes
## 342 129 277 First born 27.00000 68 130 Yes
## 343 133 292 First born 30.00000 65 112 Yes
## 344 110 277 First born 25.00000 61 130 Not
## 345 105 276 First born 22.00000 67 130 Not
## 346 93 246 First born 37.00000 65 130 Not
## 347 122 281 First born 42.00000 63 103 Yes
## 348 133 293 First born 23.00000 64 110 Yes
## 349 130 296 Unknown 22.00000 66 117 Yes
## 350 104 307 First born 24.00000 59 122 Not
## 351 106 278 First born 31.00000 65 110 Yes
## 352 120 281 First born 33.00000 63 113 Not
## 353 121 284 First born 27.00000 63 NA Yes
## 354 118 276 Unknown 18.00000 63 128 Not
## 355 140 290 Unknown 19.00000 67 132 Yes
## 356 114 268 First born 22.00000 64 104 Not
## 357 116 280 First born 40.00000 62 159 Not
## 358 129 284 First born 24.00000 64 115 Not
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## 935 119 286 First born 26.00000 64 123 Yes
## 936 97 279 First born 29.00000 68 178 Yes
## 937 99 252 First born 21.00000 64 120 Not
## 938 115 264 Unknown 23.00000 67 134 Yes
## 939 139 284 First born 37.00000 61 121 Not
## 940 144 304 Unknown 27.00000 58 102 Yes
## 941 99 270 First born 22.00000 63 115 Yes
## 942 105 280 Unknown 22.00000 63 116 Not
## 943 89 275 First born 34.00000 66 170 Not
## 944 129 270 First born 43.00000 67 160 Not
## 945 119 270 Unknown 20.00000 64 109 Not
## 946 114 291 First born 35.00000 60 112 Not
## 947 106 289 First born 28.00000 67 120 Yes
## 948 122 292 Unknown 34.00000 65 133 Not
## 949 136 261 First born 24.00000 65 110 Not
## 950 121 286 Unknown 22.00000 69 130 Yes
## 951 112 282 First born 26.00000 65 122 Not
## 952 112 266 First born 26.00000 64 122 Not
## 953 123 314 First born 22.00000 61 121 Yes
## 954 139 286 First born 33.00000 65 125 Yes
## 955 125 290 First born 36.00000 59 105 Not
## 956 105 295 Unknown 20.00000 64 112 Yes
## 957 130 276 First born 41.00000 68 130 Not
## 958 146 294 First born 22.00000 66 145 Yes
## 959 133 290 First born 21.00000 64 145 Not
## 960 147 296 Unknown 19.00000 67 124 Not
## 961 109 269 First born 23.00000 63 113 Not
## 962 122 286 First born 23.00000 64 120 Yes
## 963 135 260 First born 43.00000 65 135 Not
## 964 107 280 First born 19.00000 60 118 Not
## 965 117 272 First born 32.00000 66 118 Not
## 966 138 284 First born 30.00000 66 133 Yes
## 967 120 283 First born 28.00000 64 122 Yes
## 968 119 273 First born 35.00000 65 125 Yes
## 969 118 278 Unknown 19.00000 62 126 Not
## 970 105 330 First born 23.00000 64 112 Yes
## 971 113 306 Unknown 21.00000 65 137 Not
## 972 136 280 First born 36.00000 66 135 Not
## 973 148 291 Unknown 21.00000 63 115 Not
## 974 140 281 Unknown 22.00000 69 135 Not
## 975 134 287 Unknown 33.00000 67 131 Not
## 976 120 280 First born 31.00000 61 111 Not
## 977 123 296 Unknown 26.00000 64 110 Yes
## 978 102 275 First born 43.00000 64 160 Not
## 979 55 204 First born 35.00000 65 140 Not
## 980 103 276 Unknown 19.00000 63 149 Yes
## 981 123 283 First born 21.00000 65 110 Not
## 982 105 270 Unknown 27.00000 65 134 Yes
## 983 138 289 First born 33.00000 65 155 Not
## 984 128 281 First born 28.00000 63 150 Not
## 985 139 285 First born 30.00000 65 129 Yes
## 986 104 288 Unknown 27.00000 61 122 Yes
## 987 159 296 Unknown 27.00000 64 112 Not
## 988 118 276 First born 29.00000 62 130 Yes
## 989 99 285 First born 25.00000 69 128 Yes
## 990 144 281 First born 20.00000 63 120 Not
## 991 121 270 First born 25.00000 62 108 Yes
## 992 117 265 Unknown 24.00000 66 98 Not
## 993 119 293 Unknown 23.00000 65 127 Not
## 994 105 281 Unknown 19.00000 61 130 Not
## 995 125 283 First born 37.00000 63 145 Yes
## 996 119 259 First born 37.00000 62 130 Not
## 997 101 273 First born 39.00000 60 113 Not
## 998 105 277 Unknown 25.00000 64 156 Not
## 999 110 281 First born 27.00000 60 110 Not
## 1000 100 270 Unknown 21.00000 65 132 Yes
## 1001 98 284 First born 29.00000 68 140 Not
## 1002 127 276 First born 37.00000 64 159 Not
## 1003 117 324 First born 22.00000 62 164 Yes
## 1004 122 278 First born 37.00000 68 114 Not
## 1005 122 273 Unknown 23.00000 64 130 Yes
## 1006 118 281 Unknown 36.00000 66 140 Yes
## 1007 137 303 Unknown 23.00000 66 127 Yes
## 1008 120 275 First born 32.00000 63 115 Yes
## 1009 143 285 First born 27.00000 68 185 Not
## 1010 108 270 First born 29.00000 67 124 Yes
## 1011 131 284 Unknown 19.00000 61 114 Yes
## 1012 110 277 First born 36.00000 61 116 Not
## 1013 105 276 First born 20.00000 62 112 Yes
## 1014 133 274 First born 30.00000 63 NA Not
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## 1016 78 258 Unknown 24.00000 66 115 Yes
## 1017 114 289 First born 36.00000 60 115 Not
## 1018 111 278 First born 29.00000 65 145 Yes
## 1019 103 250 First born 40.00000 59 140 Not
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## 1021 75 247 First born 36.00000 64 120 Yes
## 1022 169 296 First born 33.00000 67 185 Not
## 1023 94 271 First born 36.00000 61 130 Yes
## 1024 150 287 First born 36.00000 62 135 Not
## 1025 144 248 First born 30.00000 70 145 Not
## 1026 144 291 First born 28.00000 67 130 Not
## 1027 143 313 First born 20.00000 68 150 Not
## 1028 145 304 Unknown 25.00000 63 109 Yes
## 1029 121 285 First born 34.00000 64 110 Not
## 1030 105 256 First born 31.00000 66 142 Not
## 1031 134 286 First born 25.00000 64 125 Not
## 1032 129 294 Unknown 21.00000 65 132 Not
## 1033 114 276 First born 24.00000 63 110 Not
## 1034 97 265 First born 30.00000 61 110 Not
## 1035 160 292 First born 28.00000 64 120 Not
## 1036 65 237 First born 31.00000 67 130 Not
## 1037 145 288 First born 28.00000 64 116 Not
## 1038 95 273 First born 23.00000 60 90 Not
## 1039 139 293 Unknown 21.00000 69 130 Not
## 1040 123 288 First born 27.00000 63 125 Not
## 1041 109 283 First born 23.00000 65 112 Yes
## 1042 110 268 First born 34.00000 64 127 Not
## 1043 122 296 Unknown 24.00000 65 132 Not
## 1044 115 307 First born 34.00000 65 128 Yes
## 1045 117 323 First born 26.00000 62 NA Not
## 1046 108 279 Unknown 19.00000 64 115 Not
## 1047 120 287 First born 23.00000 67 116 Yes
## 1048 131 269 First born 36.00000 68 145 Not
## 1049 136 283 Unknown 24.00000 63 119 Not
## 1050 125 290 First born 32.00000 63 135 Not
## 1051 96 285 Unknown 20.00000 66 117 Yes
## 1052 102 282 Unknown 29.00000 65 125 Yes
## 1053 102 288 Unknown 18.00000 65 117 Not
## 1054 112 277 Unknown 22.00000 67 120 Not
## 1055 135 272 First born 30.00000 65 130 Not
## 1056 91 266 First born 23.00000 60 120 Yes
## 1057 129 276 First born 31.00000 63 125 Not
## 1058 155 290 First born 26.00000 66 129 Yes
## 1059 109 274 First born 33.00000 69 144 Yes
## 1060 80 262 Unknown 31.00000 61 100 Yes
## 1061 125 273 First born 30.00000 64 145 Not
## 1062 94 284 First born 24.00000 63 104 Yes
## 1063 148 281 First born 27.00000 63 110 Yes
## 1064 73 277 First born 29.00000 65 145 Not
## 1065 123 267 Unknown 19.00000 66 132 Yes
## 1066 65 232 First born 24.00000 66 125 Yes
## 1067 118 279 Unknown 21.00000 64 108 Not
## 1068 102 283 First born 39.00000 60 119 Not
## 1069 120 280 First born 24.00000 61 118 Not
## 1070 108 270 Unknown 21.00000 65 130 Yes
## 1071 122 280 Unknown 45.00000 62 128 Not
## 1072 103 268 First born 32.00000 62 97 Yes
## 1073 105 312 First born 41.00000 61 115 Yes
## 1074 126 273 Unknown 25.00000 68 135 Not
## 1075 145 316 First born 22.00000 67 142 Not
## 1076 139 293 First born 34.00000 66 131 Not
## 1077 124 290 First born 26.00000 65 165 Not
## 1078 121 282 First born 30.00000 65 122 Not
## 1079 126 299 Unknown 21.00000 60 114 Not
## 1080 119 286 Unknown 33.00000 67 137 Not
## 1081 114 277 Unknown 19.00000 63 107 Not
## 1082 118 272 First born 23.00000 64 113 Not
## 1083 127 295 First born 36.00000 65 145 Not
## 1084 117 290 Unknown 22.00000 67 110 Not
## 1085 137 277 First born 41.00000 65 126 Not
## 1086 133 292 First born 29.00000 65 135 Not
## 1087 100 264 First born 28.00000 60 111 Yes
## 1088 107 273 Unknown 26.00000 65 135 Not
## 1089 115 276 Unknown 20.00000 62 105 Yes
## 1090 91 292 Unknown 26.00000 61 113 Yes
## 1091 112 287 First born 27.00000 64 110 Yes
## 1092 125 289 Unknown 31.00000 61 120 Not
## 1093 157 291 First born 33.00000 65 121 Not
## 1094 108 256 Unknown 26.00000 67 130 Not
## 1095 130 279 First born 31.00000 62 122 Not
## 1096 135 289 First born 25.00000 64 127 Not
## 1097 123 277 First born 24.00000 66 122 Not
## 1098 100 281 First born 24.00000 61 115 Not
## 1099 124 277 Unknown 23.00000 64 104 Not
## 1100 174 284 First born 39.00000 65 163 Not
## 1101 129 278 First born 26.00000 67 146 Not
## 1102 119 275 First born 27.00000 59 113 Yes
## 1103 126 272 Unknown 35.00000 61 120 Yes
## 1104 128 267 First born 37.00000 61 142 Not
## 1105 116 282 Unknown 19.00000 64 124 Not
## 1106 100 285 First born 18.00000 68 127 Yes
## 1107 96 285 First born 37.00000 66 135 Yes
## 1108 131 279 Unknown 20.00000 68 122 Yes
## 1109 110 292 First born 35.00000 62 127 Not
## 1110 108 278 First born 28.00000 63 125 Yes
## 1111 129 275 First born 24.00000 65 135 Not
## 1112 141 285 First born 23.00000 67 150 Not
## 1113 110 276 First born 31.00000 70 155 Not
## 1114 118 273 First born 21.00000 63 120 Not
## 1115 111 267 Unknown 24.00000 60 115 Not
## 1116 160 297 First born 20.00000 68 136 Not
## 1117 120 280 First born 30.00000 60 115 Not
## 1118 121 281 First born 29.00000 63 108 Not
## 1119 113 282 First born 30.00000 64 118 Yes
## 1120 117 270 First born 23.00000 58 115 Not
## 1121 158 267 First born 35.00000 64 125 Not
## 1122 128 277 First born 39.00000 61 120 Not
## 1123 158 289 First born 30.00000 66 140 Not
## 1124 133 289 First born 22.00000 65 123 Yes
## 1125 163 298 First born 37.00000 61 98 Not
## 1126 128 282 Unknown 19.00000 66 118 Not
## 1127 126 271 Unknown 21.00000 60 105 Not
## 1128 127 283 First born 42.00000 62 154 Yes
## 1129 134 287 First born 40.00000 63 118 Not
## 1130 140 274 First born 41.00000 63 122 Not
## 1131 102 285 First born 29.00000 63 117 Yes
## 1132 100 252 First born 24.00000 61 150 Not
## 1133 120 295 First born 29.00000 59 100 Yes
## 1134 98 279 Unknown 18.00000 65 115 Yes
## 1135 130 246 First born 19.00000 62 118 Not
## 1136 104 280 First born 41.00000 63 118 Yes
## 1137 122 285 First born 31.00000 62 102 Yes
## 1138 137 276 Unknown 25.00000 64 127 Not
## 1139 114 285 Unknown 20.00000 61 104 Not
## 1140 63 236 Unknown 24.00000 58 99 Not
## 1141 98 318 First born 23.00000 63 107 Not
## 1142 99 268 First born 32.00000 63 124 Yes
## 1143 89 238 Unknown 26.00000 64 136 Not
## 1144 117 283 First born 22.00000 65 142 Yes
## 1145 143 281 First born 29.00000 67 132 Not
## 1146 106 279 First born 29.00000 63 125 Yes
## 1147 99 246 First born 35.00000 62 106 Not
## 1148 156 300 First born 27.00000 65 120 Yes
## 1149 72 266 Unknown 25.00000 66 200 Yes
## 1150 75 266 First born 37.00000 61 113 Yes
## 1151 97 285 First born 35.00000 61 112 Yes
## 1152 106 264 First born 41.00000 64 114 Not
## 1153 91 225 First born 18.00000 68 117 Yes
## 1154 117 269 Unknown 28.00000 61 99 Not
## 1155 117 284 First born 25.00000 66 177 Yes
## 1156 112 291 First born 23.00000 66 145 Not
## 1157 112 270 First born 29.00000 61 124 Not
## 1158 141 293 First born 28.00000 61 125 Not
## 1159 131 259 First born 19.00000 63 134 Not
## 1160 130 290 First born 19.00000 65 123 Yes
## 1161 132 270 First born 26.00000 67 140 Not
## 1162 114 265 First born 23.00000 67 130 Yes
## 1163 160 291 First born 34.00000 64 110 Yes
## 1164 106 283 First born 24.00000 63 119 Not
## 1165 84 260 Unknown 20.00000 64 104 Yes
## 1166 112 268 Unknown 25.00000 59 103 Not
## 1167 139 311 First born 37.00000 66 135 Not
## 1168 104 267 First born 30.00000 63 180 Not
## 1169 130 294 First born 32.00000 63 110 Yes
## 1170 71 254 First born 19.00000 61 145 Yes
## 1171 82 270 First born 21.00000 65 150 Yes
## 1172 119 280 Unknown 21.00000 64 128 Not
## 1173 123 353 First born 26.00000 63 115 Not
## 1174 115 278 First born 27.00000 59 95 Not
## 1175 124 289 Unknown 21.00000 67 145 Yes
## 1176 138 292 First born 25.00000 65 130 Yes
## 1177 88 276 First born 25.00000 63 103 Yes
## 1178 146 305 First born 23.00000 NA NA Not
## 1179 128 241 Unknown 17.00000 64 126 Not
## 1180 82 274 First born 31.00000 64 101 Yes
## 1181 100 274 First born 24.00000 63 113 Not
## 1182 114 271 First born 32.00000 61 130 Not
## 1183 97 269 First born 20.00000 65 137 Yes
## 1184 126 298 First born 24.00000 61 112 Not
## 1185 122 275 Unknown 20.00000 65 127 Not
## 1186 152 295 First born 39.00000 62 140 Not
## 1187 116 274 First born 21.00000 62 110 Yes
## 1188 132 302 First born 36.00000 63 145 Yes
## 1189 84 260 Unknown 37.00000 66 140 Not
## 1190 119 277 Unknown 18.00000 61 89 Yes
## 1191 104 275 First born 24.00000 NA NA Not
## 1192 106 312 First born 24.00000 62 135 Yes
## 1193 124 280 Unknown 39.00000 65 228 Not
## 1194 139 291 First born 24.00000 65 160 Not
## 1195 103 273 First born 36.00000 65 158 Yes
## 1196 112 299 First born 24.00000 67 145 Yes
## 1197 96 276 First born 33.00000 64 127 Yes
## 1198 102 281 Unknown 19.00000 67 135 Yes
## 1199 120 300 First born 34.00000 63 150 Yes
## 1200 102 338 First born 19.00000 64 170 Not
## 1201 97 255 Unknown 22.00000 63 107 Yes
## 1202 113 285 First born 22.00000 70 145 Not
## 1203 130 297 First born 32.00000 58 130 Not
## 1204 97 260 Unknown 25.00000 63 115 Yes
## 1205 116 273 First born 31.00000 61 120 Not
## 1206 114 266 First born 29.00000 64 113 Not
## 1207 127 242 First born 17.00000 61 135 Yes
## 1208 87 247 Unknown 18.00000 66 125 Yes
## 1209 141 281 First born 29.00000 54 156 Yes
## 1210 144 283 Unknown 25.00000 66 140 Not
## 1211 116 273 First born 33.00000 66 130 Yes
## 1212 75 265 First born 21.00000 65 103 Yes
## 1213 138 286 Unknown 28.00000 68 120 Not
## 1214 99 271 First born 39.00000 69 151 Not
## 1215 118 293 First born 21.00000 63 103 Not
## 1216 152 267 First born 28.00000 NA 119 Yes
## 1217 97 266 First born 24.00000 62 109 Not
## 1218 146 319 First born 28.00000 66 145 Not
## 1219 81 285 First born 19.00000 63 150 Yes
## 1220 110 321 First born 28.00000 66 180 Not
## 1221 135 284 Unknown 19.00000 60 95 Not
## 1222 114 290 Unknown 21.00000 65 120 Yes
## 1223 124 288 Unknown 21.00000 64 116 Yes
## 1224 115 262 Unknown 23.00000 64 136 Yes
## 1225 143 281 First born 28.00000 65 135 Yes
## 1226 113 287 Unknown 29.00000 70 145 Yes
## 1227 109 244 Unknown 21.00000 63 102 Yes
## 1228 103 278 First born 30.00000 60 87 Yes
## 1229 118 276 First born 34.00000 64 116 Not
## 1230 127 290 First born 27.00000 65 121 Not
## 1231 132 270 First born 27.00000 65 126 Not
## 1232 113 275 Unknown 27.00000 60 100 Not
## 1233 128 265 First born 24.00000 67 120 Not
## 1234 130 291 First born 30.00000 65 150 Yes
## 1235 125 281 Unknown 21.00000 65 110 Not
## 1236 117 297 First born 38.00000 65 129 NotVisualización de datos
Boxplot
#Caja de bigotes
boxplot## function (x, ...)
## UseMethod("boxplot")
## <bytecode: 0x00000260bbd3c8c8>
## <environment: namespace:graphics>edades <- c(18, 22, 21, 25, 20, 22, 24, 26, 28, 22, 23, 40)
boxplot(edades,
main = "Boxplot de edades",
ylab = "Edad",
col = "pink")
min(edades)## [1] 18max(edades)## [1] 40Histogramas
#Histograma
edades <- c(18, 22, 21, 25, 20, 22, 24, 26, 28, 22, 23)
hist(edades,
main = "Distribución de edades",
xlab = "Edad",
col = "skyblue",
border = "black")
Plot
#Grafico de Lineas,tiene que haber una varible de tiempo
altura <-c(160, 165, 170, 175, 180)
peso <-c(55, 60, 65, 72, 80)
plot(altura,peso,
main="Altura vs Peso",
xlab="Altura (cm)",
ylab="Peso (Kg)",
col= "red",
pch = 19)
plot(altura, peso, type= "o")
Barplot
#Ejemplo 1
frutas <- c("Manzana", "Banana", "Pera", "Uva")
ventas <- c(30, 45, 25, 50)
barplot(ventas, names.arg = frutas,
main = "Ventas por tipo de fruta",
col = "orange",
ylab = "Cantidad")
#Barras apiladas
ventas <- matrix(c(10, 15, 20, 8, 12, 18), nrow = 2, byrow = TRUE)
colnames(ventas) <- c("Ene", "Feb", "Mar")
rownames(ventas) <- c("Producto A", "Producto B")
barplot(ventas,
beside = FALSE,
main = "Ventas mensuales por producto",
col = c("blue", "red"),
legend = rownames(ventas))
#Barras Lado a Lado(agrupadas)
ventas <- matrix(c(10, 15, 20, 8, 12, 18), nrow = 2, byrow = TRUE)
colnames(ventas) <- c("Ene", "Feb", "Mar")
rownames(ventas) <- c("Producto A", "Producto B")
barplot(ventas,
beside = TRUE,
main = "Ventas mensuales por producto",
col = c("blue", "red"),
legend = rownames(ventas))
Grafico de pastel o Pie
#Gráfico de Pastel(Pie Chart)
categorias<-c("Aprobados","Reprobados","Retirados")
valores<-c(50,30,20)
pie(valores,labels=categorias,
main="Resultados de los estudiantes",
col=c("green","red","yellow"))
Uso de ggplot2
library(ggplot2)
datos <- data.frame(
altura = c(160, 165, 170, 175, 180),
peso = c(55, 60, 65, 72, 80)
)
ggplot(datos, aes(x = altura, y = peso)) +
geom_point(color = "blue") +
ggtitle("Altura vs Peso") +
xlab("Altura (cm)") +
ylab("Peso (kg)")
Medidas de tendencia central
Estadistica Inferencial
La Estadística Inferencial es la rama de la estadística que se encarga de generalizar conclusiones a partir de una muestra hacia una población, utilizando técnicas como estimación, pruebas de hipótesis y modelos predictivos. A diferencia de la estadística descriptiva (que solo resume datos), la inferencial permite tomar decisiones bajo incertidumbre.
#Generación de hipótesis #Definición de formulación de suposiciones comprobantes estadisticamente #H_0(Hipotesis Nula) #H_1(Hipótesis alterna)
library(readxl)
Natalidad <- read_excel("C:/Users/dhoyo/Downloads/Tasa de natalidad - Nacional, Huila y municipios (1).xlsx",
sheet = "Hoja2")
View(Natalidad)
print(Natalidad)## # A tibble: 37 × 7
## `Código DANE` Territorio Regional Año Nacimientos Población
## <dbl> <chr> <chr> <dbl> <dbl> <dbl>
## 1 41006 Acevedo Sur 2005 742 20548
## 2 41013 Agrado Centro 2005 173 7868
## 3 41016 Aipe Norte 2005 332 13670
## 4 41020 Algeciras Norte 2005 499 21028
## 5 41026 Altamira Centro 2005 68 3663
## 6 41078 Baraya Norte 2005 152 8237
## 7 41132 Campoalegre Norte 2005 699 29210
## 8 41206 Colombia Norte 2005 127 8351
## 9 41244 Elías Sur 2005 61 3647
## 10 41298 Garzón Centro 2005 1566 60676
## # ℹ 27 more rows
## # ℹ 1 more variable: `Tasa de natalidad` <dbl>Hipotesis nula o alterna y su distribución de normalidad
H_0 = No existe una relación significativa entre el tamaño de la población y la tasa de natalidad en los municipios del departamento de Huila en el año 2005.
H_a = Existe una relación significativa entre el tamaño de la población y la tasa de natalidad en los municipios del departamento de Huila en el año 2005, donde municipios con mayor población tienden a tener tasas de natalidad mayores en comparación con aquellos de menor población.
shapiro.test(Natalidad$Población)##
## Shapiro-Wilk normality test
##
## data: Natalidad$Población
## W = 0.37547, p-value = 2.194e-11shapiro.test(Natalidad$`Tasa de natalidad`)##
## Shapiro-Wilk normality test
##
## data: Natalidad$`Tasa de natalidad`
## W = 0.95271, p-value = 0.118P-value > 0,05; se distribuye normalmente,como sabemos que la H_0 sigue una distribución normal y la H_a no sigue una distribución normal.
Como podemos ver que Natalidad$Población no sigue una distribución normal,decimos que rechazamos la hipotesis nula y aceptamos la alterna.
Como mis datos no siguen una distribución normal, aplicamos una prueba no parámetrica, en este caso Spearman.
Prueba de correlación
cor.test(Natalidad$Población,Natalidad$`Tasa de natalidad`, datos=Natalidad, method = "spearman")##
## Spearman's rank correlation rho
##
## data: Natalidad$Población and Natalidad$`Tasa de natalidad`
## S = 4584, p-value = 0.004888
## alternative hypothesis: true rho is not equal to 0
## sample estimates:
## rho
## 0.4566145Según nuestra correlación obtenida que es 0,4566145 decimos que tiene una correlación positiva débil y como mi P-value < 0,05 decimos que rechazamos la alterna y aceptamos la nula.
Verificación de la distribución normal de los datos
library(ggplot2)
plot( Natalidad$Población,
col="green",main="Distribución de Normalidad de Población",
xlab="Población")
plot( Natalidad$`Tasa de natalidad`,
col="red",main="Distribución de Normalidad de Tasa de Natalidad",
xlab="Tasa de Natalidad")
pairs(Natalidad$Población ~ Natalidad$`Tasa de natalidad`,
col="blue")
Aqui vemos como la distribución de la población no sigue una normalidad y la tasa de natalidad si, comparando los datos en la tercera grafica vemos que no tienen ninguna correlación significativa.
Estadistica Parametrica y No Parametrica
Pruebas parametricas
Prueba t de Student
La prueba t de Student es una herramienta estadística usada para determinar si hay una diferencia significativa entre las medias de dos grupos, bajo el supuesto de que las muestras provienen de poblaciones con distribución normal. Es especialmente útil cuando el tamaño de muestra es pequeño (generalmente n < 30).
H_0: Las medias de dos grupos son iguales.
H_1: Las medias de dos grupos son diferentes.
grupo1<-rnorm(30,mean = 8)
grupo2<-rnorm(30,mean = 9)
t.test(grupo1,grupo2)##
## Welch Two Sample t-test
##
## data: grupo1 and grupo2
## t = -3.3742, df = 55.878, p-value = 0.001351
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## -1.4985439 -0.3820139
## sample estimates:
## mean of x mean of y
## 8.045086 8.985365ANOVA
ANOVA es una técnica estadística que permite comparar las medias de tres o más grupos para determinar si al menos uno de ellos es significativamente diferente de los demás.
H0: Todas las medias de los grupos son iguales.
H1: Al menos una media de grupo es diferente.
grupo1<-rnorm(30,mean = 8)
grupo2<-rnorm(30,mean = 9)
grupo3<-rnorm(30,mean = 7)
dataAnova <- data.frame(value = c(grupo1, grupo2, grupo3),
group = factor(rep(1:3, each = 30)))
dataAnova## value group
## 1 8.634362 1
## 2 8.412022 1
## 3 8.793585 1
## 4 7.847589 1
## 5 7.771104 1
## 6 7.099208 1
## 7 7.264974 1
## 8 6.572314 1
## 9 8.619284 1
## 10 7.993802 1
## 11 7.314293 1
## 12 7.720666 1
## 13 7.217270 1
## 14 7.221003 1
## 15 7.625200 1
## 16 7.680606 1
## 17 8.084544 1
## 18 7.231526 1
## 19 7.374089 1
## 20 7.099129 1
## 21 8.663729 1
## 22 8.300279 1
## 23 8.074857 1
## 24 8.206373 1
## 25 7.511077 1
## 26 7.372048 1
## 27 7.953083 1
## 28 8.162618 1
## 29 9.292306 1
## 30 7.536443 1
## 31 9.305463 2
## 32 8.916011 2
## 33 9.410363 2
## 34 9.183678 2
## 35 10.778742 2
## 36 9.037683 2
## 37 10.176220 2
## 38 8.441464 2
## 39 8.054382 2
## 40 8.334811 2
## 41 9.452030 2
## 42 9.526856 2
## 43 8.769738 2
## 44 10.397427 2
## 45 10.763653 2
## 46 9.485601 2
## 47 8.734261 2
## 48 9.151611 2
## 49 10.376610 2
## 50 8.819606 2
## 51 7.432325 2
## 52 8.739274 2
## 53 9.961810 2
## 54 9.853895 2
## 55 9.418797 2
## 56 9.339957 2
## 57 9.596425 2
## 58 10.871418 2
## 59 9.602870 2
## 60 8.233831 2
## 61 6.379674 3
## 62 7.790190 3
## 63 6.758023 3
## 64 8.117486 3
## 65 8.184931 3
## 66 8.646475 3
## 67 7.192996 3
## 68 6.607446 3
## 69 7.007051 3
## 70 4.505165 3
## 71 6.022704 3
## 72 7.628569 3
## 73 6.915860 3
## 74 7.382132 3
## 75 5.906586 3
## 76 6.244536 3
## 77 6.736007 3
## 78 6.247537 3
## 79 7.440692 3
## 80 5.722549 3
## 81 8.177192 3
## 82 7.902506 3
## 83 5.738696 3
## 84 7.837455 3
## 85 4.651710 3
## 86 7.610971 3
## 87 6.952132 3
## 88 4.600802 3
## 89 6.980681 3
## 90 6.911315 3anova_result <- aov(value ~ group, data = dataAnova)
summary(anova_result)## Df Sum Sq Mean Sq F value Pr(>F)
## group 2 96.03 48.02 64.22 <2e-16 ***
## Residuals 87 65.05 0.75
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1Correlación de Pearson
La correlación de Pearson mide la fuerza y dirección de una relación lineal entre dos variables cuantitativas. Es uno de los métodos más usados en estadística para analizar cómo se relacionan dos variables.
H0: No hay correlación entre las variables. H1: Hay correlación entre las variables.
x <- rnorm(50)
y <- 2*x + rnorm(50)
cor.test(x, y, method = "pearson")##
## Pearson's product-moment correlation
##
## data: x and y
## t = 14.979, df = 48, p-value < 2.2e-16
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
## 0.8419896 0.9467802
## sample estimates:
## cor
## 0.9076217Regresión lineal (paramétrico)
La regresión lineal es una técnica estadística que modela la relación entre una variable dependiente Y y una o más variables independientes X. Su objetivo es predecir o explicar el comportamiento de Y en función de X.
H0: La pendiente es cero (no hay relación lineal). H1: La pendiente no es cero (hay relación lineal).
x <- rnorm(100)
y <- 2*x + rnorm(100)
model <- lm(y ~ x)
summary(model)##
## Call:
## lm(formula = y ~ x)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.8737 -0.7840 0.1298 0.7353 2.5002
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -0.09912 0.10738 -0.923 0.358
## x 2.10851 0.11276 18.699 <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.073 on 98 degrees of freedom
## Multiple R-squared: 0.7811, Adjusted R-squared: 0.7788
## F-statistic: 349.7 on 1 and 98 DF, p-value: < 2.2e-16Prueba F de Fisher
La prueba F se utiliza para evaluar si las varianzas de dos poblaciones (A yB) son iguales.
¿Cuándo se utiliza la prueba F?
La comparación de dos varianzas es útil en varios casos, entre ellos: Cuando desee realizar una prueba t de dos muestras para comprobar la igualdad de las varianzas de las dos muestras cuando se desea comparar la variabilidad de un nuevo método de medición con uno antiguo. ¿El nuevo método reduce la variabilidad de la medida?
Hipótesis nula (H₀): Las varianzas de los ingresos mensuales son iguales en zonas urbanas y rurales.
Hipótesis alternativa (H₁): Las varianzas de los ingresos mensuales son diferentes entre las zonas.
# Crear el dataframe
datos <- data.frame(
zona = c(rep("Urbana", 25), rep("Rural", 25)),
ingreso = c(1200000, 1800000, 2500000, 1600000, 2100000,
1900000, 2300000, 1700000, 2000000, 1500000,
2400000, 1800000, 2200000, 1600000, 2100000,
1900000, 2300000, 1700000, 2000000, 1500000,
2400000, 1800000, 2200000, 1600000, 2100000,
800000, 1000000, 1200000, 900000, 1100000,
950000, 1050000, 1150000, 1000000, 1100000,
850000, 1050000, 1200000, 900000, 1100000,
950000, 1050000, 1150000, 1000000, 1100000,
850000, 1050000, 1200000, 900000, 1100000)
)
# Separar los ingresos por zona
ingresos_urbano <- datos$ingreso[datos$zona == "Urbana"]
ingresos_rural <- datos$ingreso[datos$zona == "Rural"]
# Prueba de normalidad de Shapiro-Wilk
shapiro.test(ingresos_urbano)##
## Shapiro-Wilk normality test
##
## data: ingresos_urbano
## W = 0.97469, p-value = 0.7641shapiro.test(ingresos_rural)##
## Shapiro-Wilk normality test
##
## data: ingresos_rural
## W = 0.95071, p-value = 0.2602# Aplicar la prueba F de Fisher
var.test(ingresos_urbano, ingresos_rural)##
## F test to compare two variances
##
## data: ingresos_urbano and ingresos_rural
## F = 8.2065, num df = 24, denom df = 24, p-value = 2.291e-06
## alternative hypothesis: true ratio of variances is not equal to 1
## 95 percent confidence interval:
## 3.616356 18.622858
## sample estimates:
## ratio of variances
## 8.206515boxplot(ingreso ~ zona, data = datos,
main = "Distribución de Ingresos por Zona",
xlab = "Zona",
ylab = "Ingreso Mensual (COP)",
col = c("lightblue", "lightgreen"),
border = "darkgray")
Si el valor p obtenido es menor que el nivel de significancia (por ejemplo, 0.05), se rechaza la hipótesis nula, indicando una diferencia significativa en la variabilidad de los ingresos entre las zonas.
Pruebas no parametricas
Wilcoxon Rank-Sum Test
El Wilcoxon Rank-Sum Test es una prueba no paramétrica que se utiliza para comparar si dos muestras independientes provienen de la misma distribución. Es una alternativa a la prueba t de Student para muestras independientes, especialmente cuando no se cumple el supuesto de normalidad.
H0: Las distribuciones medianas de dos grupos son iguales. H1: Las distribuciones de dos grupos son diferentes.
grupo1<-rnorm(30,mean = 8)
grupo2<-rnorm(30,mean = 9)
wilcox.test(grupo1, grupo2)##
## Wilcoxon rank sum exact test
##
## data: grupo1 and grupo2
## W = 145, p-value = 2.05e-06
## alternative hypothesis: true location shift is not equal to 0Kruskal-Wallis Test
La prueba de Kruskal-Wallis es una prueba no paramétrica que se usa para comparar tres o más grupos independientes y determinar si provienen de la misma población. Es una alternativa a ANOVA de un factor, pero sin requerir normalidad ni igualdad de varianzas.
H0: Las distribuciones de todos los grupos son iguales. H1: Al menos una distribución de grupo es diferente.
grupo1<-rnorm(30,mean = 8)
grupo2<-rnorm(30,mean = 9)
grupo3<-rnorm(30,mean = 7)
data <- data.frame(value = c(grupo1, grupo2, grupo3),group = factor(rep(1:3, each = 30)))
data## value group
## 1 6.874970 1
## 2 8.120595 1
## 3 8.149818 1
## 4 7.868602 1
## 5 8.581616 1
## 6 8.053327 1
## 7 6.566523 1
## 8 5.777009 1
## 9 10.438003 1
## 10 8.941265 1
## 11 8.098949 1
## 12 7.406550 1
## 13 7.304705 1
## 14 8.570353 1
## 15 7.057792 1
## 16 7.667901 1
## 17 8.562611 1
## 18 6.900915 1
## 19 8.155948 1
## 20 9.031787 1
## 21 8.843324 1
## 22 8.329015 1
## 23 6.118321 1
## 24 7.629311 1
## 25 7.053461 1
## 26 7.781591 1
## 27 7.392894 1
## 28 6.109366 1
## 29 7.950164 1
## 30 6.588209 1
## 31 7.870845 2
## 32 9.697000 2
## 33 9.317461 2
## 34 8.158064 2
## 35 9.606060 2
## 36 9.656468 2
## 37 9.073776 2
## 38 10.535197 2
## 39 9.413916 2
## 40 9.939767 2
## 41 8.723882 2
## 42 8.307489 2
## 43 10.536321 2
## 44 9.172731 2
## 45 8.132396 2
## 46 8.514097 2
## 47 7.428478 2
## 48 9.172144 2
## 49 9.163136 2
## 50 9.914156 2
## 51 9.170645 2
## 52 9.682201 2
## 53 8.440793 2
## 54 8.355563 2
## 55 8.760513 2
## 56 10.682444 2
## 57 8.761187 2
## 58 9.327631 2
## 59 7.914768 2
## 60 9.251060 2
## 61 8.398075 3
## 62 6.673383 3
## 63 8.055361 3
## 64 6.193572 3
## 65 6.184404 3
## 66 6.298522 3
## 67 5.542355 3
## 68 6.437705 3
## 69 8.917803 3
## 70 6.751345 3
## 71 8.380644 3
## 72 7.120607 3
## 73 6.739518 3
## 74 7.344850 3
## 75 6.195393 3
## 76 8.108556 3
## 77 5.896921 3
## 78 7.801130 3
## 79 7.238551 3
## 80 7.138502 3
## 81 7.726280 3
## 82 6.141004 3
## 83 5.772416 3
## 84 6.708145 3
## 85 8.212737 3
## 86 7.577182 3
## 87 9.280428 3
## 88 5.995890 3
## 89 7.105948 3
## 90 10.057125 3kruskal.test(value ~ group, data = data)##
## Kruskal-Wallis rank sum test
##
## data: value by group
## Kruskal-Wallis chi-squared = 37.599, df = 2, p-value = 6.847e-09Chi-cuadrado
La prueba de chi-cuadrado (χ²) es una técnica estadística no paramétrica que se usa para evaluar si existe una diferencia significativa entre las frecuencias observadas y las esperadas en una o más categorías.
H0: Las variables son independientes. H1: Las variables no son independientes.
data <- matrix(c(30, 40, 40, 50,20,30,30,50), nrow = 2)
chisq.test(data)##
## Pearson's Chi-squared test
##
## data: data
## X-squared = 0.94715, df = 3, p-value = 0.814Correlación de Spearman
La correlación de Spearman es una medida no paramétrica que evalúa la relación monotónica entre dos variables. A diferencia de la correlación de Pearson, no requiere que la relación sea lineal ni que los datos sigan una distribución normal.
H0: No hay correlación entre las variables. H1: Hay correlación entre las variables.
x <- rnorm(100)
y <- 2*x + rnorm(100)
cor.test(x, y, method = "spearman")##
## Spearman's rank correlation rho
##
## data: x and y
## S = 22674, p-value < 2.2e-16
## alternative hypothesis: true rho is not equal to 0
## sample estimates:
## rho
## 0.8639424Test de Fisher
La prueba exacta de Fisher es una prueba estadística no paramétrica que se utiliza para determinar si hay una asociación significativa entre dos variables categóricas en una tabla de contingencia 2x2. Es especialmente útil cuando los tamaños de muestra son pequeños y no se cumplen los requisitos para usar la prueba chi-cuadrado.
H0: Las variables son independientes. H1: Las variables no son independientes.
data <- matrix(c(1, 2, 3, 4), nrow = 2)
fisher.test(data)##
## Fisher's Exact Test for Count Data
##
## data: data
## p-value = 1
## alternative hypothesis: true odds ratio is not equal to 1
## 95 percent confidence interval:
## 0.008512238 20.296715040
## sample estimates:
## odds ratio
## 0.693793