Proof

While the data scientist may not directly refer to formal mathematical proofs in their daily work, they may find that the principles and logic of (someone&s;s) mathematical proofs either corroborate or contradict the conclusions of their data analysis. Therefore, it behooves the data scientist to have some exposure to methods of proof. The concept of proof can take various analytical forms. Mathematicians use prepositional logic for constructing statements that form proofs. Data science is more concerned with empirical proof or evidence based on observed conditions from sets of data. However, observation is not always immediately feasible, as data collection and computation can take significant time. Thus, empirical and logical approaches can be used to corroborate one another.