Hello, the aim of the starter notebook is to introduce statistical learning as well as data science methodologies to a broad audience. This audience consists of people that have never even coded before.

The linear model is there to illustrate how a linear model can be implemented for a specific dataset. This model can be altered to predict sub-category values if you just change the dataset accordingly. Remember, the dataset used for the linear model contains headline CPI values, therefore the output of the linear model will be headline CPI. The month does not matter. 

It is your job to figure this out from the information given.

The weighting system is an introduction to the prediction of the sub-categories and illustrate the weighting system for sub-category CPI values.

The aim of the starter notebooks is not to solve the problem at hand but rather to aid your journey to a solution.



Just remember, complex models are not always better.

Here is a great introduction video series to statistical learning: https://www.youtube.com/watch?v=5N9V07EIfIg&list=PLOg0ngHtcqbPTlZzRHA2ocQZqB1D_qZ5V