Anscombe’s quartet

Install packages & libraries

#install.packages(tidyverse)
#install.packages('Tmisc')
library(tidyverse)

## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
## ✔ dplyr     1.1.4     ✔ readr     2.1.5
## ✔ forcats   1.0.0     ✔ stringr   1.5.1
## ✔ ggplot2   3.5.2     ✔ tibble    3.3.0
## ✔ lubridate 1.9.4     ✔ tidyr     1.3.1
## ✔ purrr     1.0.4     
## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## ✖ dplyr::filter() masks stats::filter()
## ✖ dplyr::lag()    masks stats::lag()
## ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors

library(Tmisc)

Quartet

Create & view a data frame

data(quartet)
#View(quartet)

Summarize the data frame quartet

Use group by & summarize to create the statiistical data frame. Use mean to calculate average, sd()= “desviacion estandar” y cor= “correlation”

quartet %>%
    group_by(set) %>%
    summarize(mean(x), sd(x), mean(y), sd(y),cor(x,y))

## # A tibble: 4 × 6
##   set   `mean(x)` `sd(x)` `mean(y)` `sd(y)` `cor(x, y)`
##   <fct>     <dbl>   <dbl>     <dbl>   <dbl>       <dbl>
## 1 I             9    3.32      7.50    2.03       0.816
## 2 II            9    3.32      7.50    2.03       0.816
## 3 III           9    3.32      7.5     2.03       0.816
## 4 IV            9    3.32      7.50    2.03       0.817

Charts

Use ggplot to paint graphs

ggplot(quartet, aes(x,y)) +
  geom_point() + 
  geom_smooth(method=lm,se=FALSE) + 
  facet_wrap(~set)

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

Packages “DatasauRus”

Other data frame interesting, that is including in DatasauRus package

#install.packages('datasauRus')
library('datasauRus')

“DatasauRus” Data frame

View the data frame

#View(datasaurus_dozen)

“DatasauRus” Data frame Graphs

ggplot(datasaurus_dozen, aes(x=x,y=y, colour=dataset))+ 
  geom_point()+ 
  theme_void()+
  theme(legend.position = "none")+
  facet_wrap(~dataset,ncol=3)