Multi-factor variance analysis

To understand the correlation between the variables, it is important to understand the interaction between all the variables within the dataset. Let's focus on multi-factor variance analysis of the data frame specified with the help of the following steps:

1. Create an aggregate value of the data frame with respect to the mpg and displacement values mentioned as follows:

> d <- aggregate(mpg ~ displacement, data = Autompg, FUN = mean)

> d    
             displacement mpg
        
          1 68.0 29.00000
          2 70.0 20.23333
          3 71.0 31.50000 
          4 72.0 35.00000
          5 76.0 31.00000
          6 78.0 32.80000
          7 79.0 32.18333
          8 80.0 21.50000
          9 81.0 35.10000
          10 83.0 32.00000
          > 
          print(abs(d[[2]][1]-d[[2]][2]))
        
          [1] 8.7666
67

2. Now, let's build a...