I have 2 datasets with details about discount percentages and failure rates. The discount rates are given for each model manufactured by a certain brand. The failure rates are given at the brand level.
Here is some dummy data: (https://i.stack.imgur.com/Keqf0.png)
(https://i.stack.imgur.com/DJ56g.png)
All data is represented for a given month and year and it is not normally distributed. A join can be made between the 2 datasets based on the brand name and date. Essentially, there will be duplicates in the resulting table and that's okay. The correlation between the discount percentages and the failure rate is 0.25. I want to know if there is any viable approach to predict the discount percentages for a brand based on the failure rates.
Any help would be really appreciated.
