Basic data analysis and predictions

[jefsummers]

Splitting will allow you to "prove your model" - create the regression using the training set, tweak the hyperparameters using validation, and prove you did it right with the test data.

Are you familiar with overfitting? That is when your model gets really good at predicting the training data but is really adjusted just for that and does poorly in predicting with the test data. That is what you want to avoid.

Using the split data helps you to avoid overfitting - if you are great with the training data but poor with validation, simplify the model.