Practice. And education, but mostly practice. This is the kind of thing that is typically taught in formal educational settings (at least in engineering, which is my experience). As an example, I learned more about probability & statistics in 1) AP biology in high school, and 2) a "simulation systems" class in my industrial engineering master's curriculum. We spent much of the former class learning basic statistical analysis techniques (ANOVA, chi-square, etc) to apply to our lab data, and the latter class was all about statistical analysis of process flows (aimed at the real life problem of factory production planning & scheduling and manufacturing process optimization).
So, do I consider myself a data scientist? Absolutely not. But do I understand basic statistical concepts and know how to apply them to several categories of real life data analysis problems.
Would you recommend any approach or I should go undust my high school and college books in the search for study material. Or is this too basic material.
So, do I consider myself a data scientist? Absolutely not. But do I understand basic statistical concepts and know how to apply them to several categories of real life data analysis problems.
I'm a terrible coder, btw.