library(dplyr)
##
## Attaching package: 'dplyr'
## The following objects are masked from 'package:stats':
##
## filter, lag
## The following objects are masked from 'package:base':
##
## intersect, setdiff, setequal, union
library(datasets)
datasets::anscombe
## x1 x2 x3 x4 y1 y2 y3 y4
## 1 10 10 10 8 8.04 9.14 7.46 6.58
## 2 8 8 8 8 6.95 8.14 6.77 5.76
## 3 13 13 13 8 7.58 8.74 12.74 7.71
## 4 9 9 9 8 8.81 8.77 7.11 8.84
## 5 11 11 11 8 8.33 9.26 7.81 8.47
## 6 14 14 14 8 9.96 8.10 8.84 7.04
## 7 6 6 6 8 7.24 6.13 6.08 5.25
## 8 4 4 4 19 4.26 3.10 5.39 12.50
## 9 12 12 12 8 10.84 9.13 8.15 5.56
## 10 7 7 7 8 4.82 7.26 6.42 7.91
## 11 5 5 5 8 5.68 4.74 5.73 6.89
colMeans(anscombe)
## x1 x2 x3 x4 y1 y2 y3 y4
## 9.000000 9.000000 9.000000 9.000000 7.500909 7.500909 7.500000 7.500909
View(anscombe)
round(sapply(anscombe, mean), 3)
## x1 x2 x3 x4 y1 y2 y3 y4
## 9.000 9.000 9.000 9.000 7.501 7.501 7.500 7.501
round(sapply(anscombe, sd), 3)
## x1 x2 x3 x4 y1 y2 y3 y4
## 3.317 3.317 3.317 3.317 2.032 2.032 2.030 2.031
round(cor(anscombe[,1:4], anscombe[5:8]), 3)
## y1 y2 y3 y4
## x1 0.816 0.816 0.816 -0.314
## x2 0.816 0.816 0.816 -0.314
## x3 0.816 0.816 0.816 -0.314
## x4 -0.529 -0.718 -0.345 0.817
lm(y1 ~ x1, data = anscombe)
##
## Call:
## lm(formula = y1 ~ x1, data = anscombe)
##
## Coefficients:
## (Intercept) x1
## 3.0001 0.5001
lm(y2 ~ x2, data = anscombe)
##
## Call:
## lm(formula = y2 ~ x2, data = anscombe)
##
## Coefficients:
## (Intercept) x2
## 3.001 0.500
lm(y3 ~ x3, data = anscombe)
##
## Call:
## lm(formula = y3 ~ x3, data = anscombe)
##
## Coefficients:
## (Intercept) x3
## 3.0025 0.4997
lm(y4 ~ x4, data = anscombe)
##
## Call:
## lm(formula = y4 ~ x4, data = anscombe)
##
## Coefficients:
## (Intercept) x4
## 3.0017 0.4999
Ozetle \[\overline{x}=9\]
\[\overline{y}=4.5\]
\[sd_\overline{x}=3.32\] \[sd_\overline{y}=4.125\]
\[cor_{xy}=0.816\] \[y = 3 + 0.5x\]
library(quartets)
library(ggplot2)
library(dplyr)
ggplot(anscombe_quartet, aes(x=x, y=y)) +
geom_point() +
geom_smooth(method= "lm", formula= "y~ x") +
facet_wrap(.~dataset)