I have a data set that I have added to and plan to carry out some modelling with. I'm wondering whether I should split the data into test / training prior to carrying out the modelling, or if I should write the descriptive section out first then split into test/training for the modelling part.
The descriptive stuff is going to be things like percentiles, some $\chi^2$ between different levels, basics like this.
The data is mainly categorical, there are around 700 rows and 30 columns. I'm planning to carry out logistic regression and (probably) a decision tree.