| >I still can't get over the term "data science", though. Not only is it ridiculously meaningless - what sort of science doesn't involve data, and how often would data be useful to something that isn't scientific at some level - its meaninglessness derives from the hyped buzzword trendiness that drove its upswing. I couldn't disagree more. There are a number of terms for domain-independent data analysis: - data analysis - statistics - statistical modeling - machine learning - big data - data journalism - data science I think it makes perfect sense that the practice of collecting and analyzing data be qualified and indentified as a specific field. I know of no better resource than these venn diagrams which identify the 'danger zones' around data science: - http://datascienceassn.org/content/fourth-bubble-data-scienc... Is there such a thing as a statistical model which only applies to a certain domain? Domain knowledge ("substantive expertise"/"social sciences" in the linked venn diagrams) serves only to logically validate statistical models which may be statistically valid but otherwise illogical, in context to currently-available field knowledge (bias). Regardless of field, the math is the same. Regardless of field, the model either fits or it doesn't. Regardless of field, the controls were either sufficient or they weren't. |