Factor Analysis: Picking the Right Variables

In layman's terms, it means choosing which factors (variables) in a data set you should use for your model. In the above example, the columns (highlighted in light orange) would be our Factors. It can be very tempting, especially for new data science students, to want to include as many factors as possible. In fact, as you add more factors to a model, you will see many classic statistical markers for model goodness increase. This can give you a false sense of trust in the model.