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>I wonder how many "data scientists" around don't know what a normal distribution is What is with the poisonous gate-keeping in the data science field/communit

>I wonder how many "data scientists" around don't know what a normal distribution is What is with the poisonous gate-keeping in the data science field/community? Is it a bunch of PhDs stuck doing marketing, bitter that people in the business domain are competing with them? What do you care if a "data scientist" doesn't know what a normal distribution is? Are you worried about them as competition? If that person is getting hired in a role over you, maybe you should look in the mirror or be happy you dodged a bullet at said company. Easy. I realize you're being facetious, but I always think back to that post here where someone asked how to become a data scientist and one of the replies said you needed to be able to code all the algorithms from scratch in C, C++, CUDA etc etc. Hilarious. The purpose of data science is solving problems with the help of data. Everything else is semantics. In the real world most of the value comes from pretty simple solutions. Most people aren't working for Google X. Most experiments aren't critical. Uncertainty is acceptable. The inane trivia --which I liken to stupid whiteboard coding challenges-- becomes less important as the tooling improves. Better get used to it, or the ambitious analysts and BI people will eat your lunch.

zimablue 8y ago
I'm not sure the normal distribution or avoiding reversion to mean fallacy are trivia though.
mumpsman 8y ago
Know how I know you've never worked on a data science project with someone who doesn't know what they are doing in the slightest? Reword your entire sentiment towards programming and you get something like this: "What do you care if a 'programmer' doesn't know what a variable is?" The reality is that, like programming, there are some simple things (throw features into a random forest and get an adequate model) but if you actually want to drive value in any data science role you must be knowledgeable about the details of what you are doing and you must know exactly how these algorithms work to avoid ruinous pitfalls.

zimablue 8y ago

I'm not sure the normal distribution or avoiding reversion to mean fallacy are trivia though.

mumpsman 8y ago

Know how I know you've never worked on a data science project with someone who doesn't know what they are doing in the slightest? Reword your entire sentiment towards programming and you get something like this: "What do you care if a 'programmer' doesn't know what a variable is?" The reality is that, like programming, there are some simple things (throw features into a random forest and get an adequate model) but if you actually want to drive value in any data science role you must be knowledgeable about the details of what you are doing and you must know exactly how these algorithms work to avoid ruinous pitfalls.