Let's say I'm working with the `iris` dataset in R:

```
data(iris)

summary(iris)
  Sepal.Length    Sepal.Width     Petal.Length    Petal.Width   
 Min.   : 4.300   Min.   : 2.000   Min.   : 1.000   Min.   : 0.100  
 1st Qu.: 5.100   1st Qu.: 2.800   1st Qu.: 1.600   1st Qu.: 0.300  
 Median : 5.800   Median : 3.000   Median : 4.350   Median : 1.300  
 Mean   : 5.843   Mean   : 3.057   Mean   : 3.758   Mean   : 1.199  
 3rd Qu.: 6.400   3rd Qu.: 3.300   3rd Qu.: 5.100   3rd Qu.: 1.800  
 Max.   : 7.900   Max.   : 4.400   Max.   : 6.900   Max.   : 2.500  
       Species  
 setosa    : 50  
 versicolor: 50  
 virginica : 50

```

I want to perform a linear regression where `Petal.Length` is the dependent variable, and `Sepal.Length` is the independent variable. How can I, in R, perform this regression for each `Species` category at once, getting values of P, R² and F for each test?