R Statistics Cookbook

How to do it...

We will work with the same dataset that we used for the previous chapter, which contains the sales in a shop, and two features (the number of people that entered the shop and the discount that was done to all clients on each day):

1. We first load the data and start with our model:

data = read.csv("./people_shopping.csv") model = lm(sales ~ people_in + discount,data=data)  library("lmtest") bptest(model) 

2. As we did on the previous recipe, we can test whether the residuals are homoscedastic:

summary(model) 

We reject the null hypothesis of homoscedasticity:

3. Let's see how the estimated model looks like (the p-value will not ...