As we did in Subsection 8.4.2, let’s first construct the bootstrap distribution for \(\widehat{p}_{seed} - \widehat{p}_{control}\) and then use this to construct 95% confidence intervals for \(p_{seed} - p_{control}\). We’ll do this using the infer workflow again. However, since the difference in proportions is a new scenario for inference, we’ll need to use some new arguments in the infer functions along the way.