TBH, I haven't used python for science in a few years, so maybe numpy is the norm now and I'm showing my age. But when I was doing more python, I wrote bootstrapping, monte carlo and CI code without anything but the standard lib. I probably used pypy to get it fast enough, but if everyone has numpy now then that's definitely the way to go and I retract my comment!

I'm not trying to sound arrogant or anything, if numpy is the standard now then there's definitely no point in reinventing the wheel. (But pandas is still overkill...)