My point is most real world problems people face (even most problems that data scientists face at work) shouldn't be modelled with formal math.
Basic reasoning, tinkering, plotting data and playing around with data in Excel or Python is usually sufficient to answer most questions, yet many will try to overcomplicate the issue with complex math or stats. Perhaps in an attempt to impress their peers, or perhaps because they've just come out of years of university that taught them to think theoretically.
Basic reasoning, tinkering, plotting data and playing around with data in Excel or Python is usually sufficient to answer most questions, yet many will try to overcomplicate the issue with complex math or stats. Perhaps in an attempt to impress their peers, or perhaps because they've just come out of years of university that taught them to think theoretically.
I'm reminded of that meme going around.
70 IQ: plot data
100 IQ: support vector machines! deep Q-nets!
130 IQ: plot data