In [5]:

    

# Carregando os pacotes
library(datasets)
library(broom)
library(ggplot2)
library(lattice)
library(QuantPsyc)


    

In [7]:

    

# Visualizando o dataset
data(iris)
str(iris)
head(iris)


    

    




'data.frame':	150 obs. of  5 variables:
 $ Sepal.Length: num  5.1 4.9 4.7 4.6 5 5.4 4.6 5 4.4 4.9 ...
 $ Sepal.Width : num  3.5 3 3.2 3.1 3.6 3.9 3.4 3.4 2.9 3.1 ...
 $ Petal.Length: num  1.4 1.4 1.3 1.5 1.4 1.7 1.4 1.5 1.4 1.5 ...
 $ Petal.Width : num  0.2 0.2 0.2 0.2 0.2 0.4 0.3 0.2 0.2 0.1 ...
 $ Species     : Factor w/ 3 levels "setosa","versicolor",..: 1 1 1 1 1 1 1 1 1 1 ...






    
Out[7]:





Sepal.Length
Sepal.Width
Petal.Length
Petal.Width
Species

	
1
5.1   
3.5   
1.4   
0.2   
setosa
	
2
4.9   
3     
1.4   
0.2   
setosa
	
3
4.7   
3.2   
1.3   
0.2   
setosa
	
4
4.6   
3.1   
1.5   
0.2   
setosa
	
5
5     
3.6   
1.4   
0.2   
setosa
	
6
5.4   
3.9   
1.7   
0.4   
setosa

In [9]:

    

# Regressão Linear Simples
# Sepal Length vs Petal Lenth
ggplot(data = iris,aes(x = Sepal.Length, y = Petal.Length)) +
  geom_point(size = 2, colour = "black") +
  geom_point(size = 1, colour = "white") +
  geom_smooth(aes(colour = "black"), method = 'lm') +
  ggtitle("Sepal Length vs Petal Length") +
  xlab("Sepal Length") + ylab("Petal Length") +
  theme(legend.position = "none")