R Statistics Cookbook

How to do it...

In this exercise, we will focus on a simple ANOVA example and show the mechanics of the sum of squares and F-tests. We will use a balanced dataset and calculate the sum of squares and the F-tests manually. The dataset will contain weight measurements for animals, and these will depend on which food type they were fed on and which lot the animals were assigned.

In R, we can compute the anova table using the anova function on a linear model that we can estimate via the lm or aov functions:

1. Load the dataset, as follows:

data = read.csv("./anova__lot_type.csv") 

2. We need to compute the sum of squares for the first factor. This is defined as the sum of squared deviations between the predictions and the target variable: