Anscombe

#codigo

# Importar los datos
anscombe <- read.csv2("anscombe.csv")
# Imprimir la estructura de datos
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 ...

uno <- subset(anscombe, Set=="1")
dos <- subset(anscombe, Set=="2")
tres <- subset(anscombe, Set=="3")
cuatro <- subset(anscombe, Set=="4")

XProm <- mean(uno$X)
YProm <- mean (uno$Y)
Xvar <- var(uno$X)
Yvar <- var(uno$Y)
Corr <- cor(uno$X, uno$Y)
# Se guardan en un dataset
SummaryStats <- data.frame(XProm, YProm, Xvar, Yvar, Corr)
SummaryStats

##   XProm    YProm Xvar     Yvar      Corr
## 1     9 7.500909   11 4.127269 0.8164205

XProm <- mean(dos$X)
YProm <- mean (dos$Y)
Xvar <- var(dos$X)
Yvar <- var(dos$Y)
Corr <- cor(dos$X, dos$Y)
SummaryStats <- data.frame(XProm, YProm, Xvar, Yvar, Corr)
SummaryStats

##   XProm    YProm Xvar     Yvar      Corr
## 1     9 7.500909   11 4.127629 0.8162365

#install.packages(ggplot2)
library(ggplot2)

#visualización

# Canvas sobre el que vamos a dibujar
plotAns <- ggplot(anscombe,aes(X,Y, color = Set))
# Diagrama de lineas
plotAns <- plotAns + geom_line()
# Regresion lineal
plotAns <- plotAns + geom_smooth(method=lm, se=FALSE)
# promedio X
plotAns <- plotAns + geom_vline (aes ( xintercept = SummaryStats[1,1]))
# promedio Y
plotAns <- plotAns + geom_hline (aes ( yintercept = SummaryStats[1,2]))
plotAns

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

# facetas
plotAns <- plotAns + facet_grid(. ~ Set)
plotAns

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