Asignacion de variables
x <- 3
y <- 2
IMPRIMIR VARIABLES
x
## [1] 3
y
## [1] 2
OPERACIONES ARITMETICAS
suma <- x+y
suma
## [1] 5
resta <- x-y
resta
## [1] 1
division <- 3/2
division
## [1] 1.5
residuo <- x%%y
residuo
## [1] 1
division_entera <- x%/% y
division_entera
## [1] 1
potencia <- x^y
potencia
## [1] 9
FUNCION MATEMATICA
raiz_cuadrada <- sqrt(x)
raiz_cuadrada
## [1] 1.732051
raiz_cubica <- x^(1/3)
raiz_cubica
## [1] 1.44225
exponencial <- exp(1)
exponencial
## [1] 2.718282
absoluto <- abs(x)
absoluto
## [1] 3
signo <- sign(x)
signo
## [1] 1
redonde_arriba <- ceiling(division)
redonde_arriba
## [1] 2
redondeo_abajo <- floor(division)
redondeo_abajo
## [1] 1
truncar <- trunc(division)
truncar
## [1] 1
CONSTANTES
pi
## [1] 3.141593
radio <- 5
area_circulo <- pi*radio^2
area_circulo
## [1] 78.53982
VECTORES
a <- c(1,2,3,4,5)
a
## [1] 1 2 3 4 5
b <- c(1:100)
b
## [1] 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18
## [19] 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36
## [37] 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54
## [55] 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72
## [73] 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90
## [91] 91 92 93 94 95 96 97 98 99 100
c <- seq(1,5, by=0.5)
c
## [1] 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0
d <- rep(1:2, times=3)
d
## [1] 1 2 1 2 1 2
e <- rep(1:2, each=3)
e
## [1] 1 1 1 2 2 2
nombre <- c("juan", "sara", "pedro")
nombre
## [1] "juan" "sara" "pedro"
nombre <- sort(nombre, decreasing = TRUE)
nombre
## [1] "sara" "pedro" "juan"
f <- c(1,2,3,4,5)
suma_vectores <- a+f
suma_vectores
## [1] 2 4 6 8 10
GRAFICAR
año <- c(2020:2025)
PIB <- c(8744, 10250, 11500, 13800, 14034, 13967)
plot(año,
PIB,
main="PIB per capita en México",
xlab = "Año",
ylab = "USD",
type = "b",
)

TABLAS
persona <- c("Raul", "Miguel", "Roberta", "Samanta", "Junior", "Meme")
altura <- c(1.80, 1.74, 1.64, 1.60, 1.69, 1.75)
peso <- c(80, 78, 55, 57, 62, 525)
df <- data.frame(persona,altura,peso)
df
## persona altura peso
## 1 Raul 1.80 80
## 2 Miguel 1.74 78
## 3 Roberta 1.64 55
## 4 Samanta 1.60 57
## 5 Junior 1.69 62
## 6 Meme 1.75 525
max(df$peso)
## [1] 525
min(df$altura)
## [1] 1.6
df[1, ]
## persona altura peso
## 1 Raul 1.8 80
df[ ,1]
## [1] "Raul" "Miguel" "Roberta" "Samanta" "Junior" "Meme"
df[2,2]
## [1] 1.74
summary(df)
## persona altura peso
## Length:6 Min. :1.600 Min. : 55.00
## Class :character 1st Qu.:1.653 1st Qu.: 58.25
## Mode :character Median :1.715 Median : 70.00
## Mean :1.703 Mean :142.83
## 3rd Qu.:1.748 3rd Qu.: 79.50
## Max. :1.800 Max. :525.00
str(df)
## 'data.frame': 6 obs. of 3 variables:
## $ persona: chr "Raul" "Miguel" "Roberta" "Samanta" ...
## $ altura : num 1.8 1.74 1.64 1.6 1.69 1.75
## $ peso : num 80 78 55 57 62 525
#LOGICO: TRUE FALSE
#FACTOR: NIVELES
#MEDIDAS DE TENDENCIA CENTRAL
#Moda(Promedio), mediana y
mean(df$peso)
## [1] 142.8333
median(df$altura)
## [1] 1.715
#MEDIDAS DE DISPERSION
#Rango, Varianza, Desviacion Estandar, COeficiente de Variacion
var(df$peso)
## [1] 35163.77
sd(df$peso)
## [1] 187.52
sd(df$altura)
## [1] 0.07447595
cv_altura <- sd(df$altura)/mean(df$altura)*100
cv_altura
## [1] 4.372365
cv_peso <- sd(df$peso)/mean(df$peso)*100
cv_peso
## [1] 131.2859
#MEDIDAS DE POSICION
#Percentiles y Cuartiles
boxplot(df$altura)

df$IMC <- peso/(altura^2)
df
## persona altura peso IMC
## 1 Raul 1.80 80 24.69136
## 2 Miguel 1.74 78 25.76298
## 3 Roberta 1.64 55 20.44914
## 4 Samanta 1.60 57 22.26562
## 5 Junior 1.69 62 21.70792
## 6 Meme 1.75 525 171.42857
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