Pearson within groups
An A/B design has the benefit of being able to run the Pearson correlation within each group to further assess the relationship based on a potential influence, the grouping.
A company is interested in assessing the relationship between the amount of time spent searching on the website and amount of money spent on items for each ad. You determined a Pearson correlation is fitting given the linearity and normal distribution, and assessed the relationship ignoring groups. Perform the Pearson correlation test within each group, New
and Old
, stored under the Ad
variable.
The SiteSales
dataset has been loaded for you.
This exercise is part of the course
A/B Testing in R
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# Run the Pearson correlation on the New ad
cor.test(___,
data = ___,
subset = ___,
method = ___)