reporteAnscombe

Cuarteto de Anscombe

#importar los datos
anscombe <- read.csv2("~/Documents/WorkspaceR/Univalle_2023/anscombe.csv")
str(anscombe)

## 'data.frame':    44 obs. of  3 variables:
##  $ Set: int  1 1 1 1 1 1 1 1 1 1 ...
##  $ X  : int  10 8 13 9 11 14 6 4 12 7 ...
##  $ Y  : num  8.04 6.95 7.58 8.81 8.33 ...

anscombe$Set <- as.factor(anscombe$Set)
str(anscombe)

## 'data.frame':    44 obs. of  3 variables:
##  $ Set: Factor w/ 4 levels "1","2","3","4": 1 1 1 1 1 1 1 1 1 1 ...
##  $ X  : int  10 8 13 9 11 14 6 4 12 7 ...
##  $ Y  : num  8.04 6.95 7.58 8.81 8.33 ...

# divididir en subgrupos
uno <- subset(anscombe,anscombe$Set == "1")
promX <- mean(uno$X)
varX <- var(uno$X)
promY <- mean(uno$Y)
varY <- var(uno$Y)
corr <- cor(uno$X, uno$Y)

Hacemos la visualizacion del primer conjunto

# instalar la libreria de ggplot

# importar la libreria
library(ggplot2)

plotUno <- ggplot(uno, aes(X, Y))

plotUno <- plotUno + geom_point()

plotUno <- plotUno + geom_smooth(method=lm, se=FALSE)

plotUno <- plotUno + geom_vline(aes(xintercept = promX))
plotUno <- plotUno + geom_hline(aes(yintercept = promY))

plotUno

## `geom_smooth()` using formula = 'y ~ x'

ggplot(anscombe) +
  aes(x = X, y = Y, colour = Set) +
  geom_point(shape = "circle", size = 1.5) +
  scale_color_hue(direction = 1) +
  theme_minimal() +
  facet_wrap(vars(Set))