Choose Your Own Data Science Adventure - René Lumley-Hall
If you find yourself wanting to know more about Data Science, related terminology, and its potential applicability in your world, you might appreciate Cassie Kozyrkov’s “Stats Gist List: An Irreverent Statistician’s Guide to Jargon.”
Here are a few snippets and one of several straightforward (and rather funny) illustrations from this brilliant and helpful piece:
⭐️ “Data science is the discipline of making data useful. Its three subdisciplines are called statistics, machine learning, and analytics.”
⭐️ “Analytics is a subdiscipline of data science that is often confused with statistics. Analytics is all about finding good questions, while statistics is all about finding good answers. The key difference is that analytics is concerned primarily with what’s in your data while statistics is concerned with what’s beyond your data.”
⭐️ “Machine Learning (ML) A discipline that’s related to statistics, but has a different focus: automation. Statistics care about rigor, inference, and coming to the right conclusion, whereas machine learning cares about performance and turning patterns in data into recipes that get the job done.”
Stats Gist List: An Irreverent Statistician’s Guide to Jargon
