i love math because my dad loves it, and from a young age taught me his way of doing math, which included solving complex operations in my head. in fact, that's often how we spent road trips. so at some level, it's a sentimental bond that we share.
of course, in school i always got in trouble for not "showing my work".
one of the reasons i love my job is because it's a marriage of left brain creative-driven, exploration of the conceptual and understanding what people respond to visually and emotionally and enough logic and linear conclusion to make a geeky girl like me very happy.
however, there's another side that's all about results, and that requires understanding metrics from a statistically significant perspective. lots of people can lie with statistics, but to make good decisions you have to know how to evaluate data and separate the wheat from the chaff. and that includes a fundamental ability to understand trends, build valuable data collection into your projects and pay attention to things like sample size and cyclical considerations that can mislead.
billions of dollars are wasted upon conclusions built upon fallacy.
in the (meaningful) data, we can find absolute truth--it's black and white, unyielding and decisive.
and there's no better feeling than making decisions on that kind of stability.
of course, in school i always got in trouble for not "showing my work".
one of the reasons i love my job is because it's a marriage of left brain creative-driven, exploration of the conceptual and understanding what people respond to visually and emotionally and enough logic and linear conclusion to make a geeky girl like me very happy.
however, there's another side that's all about results, and that requires understanding metrics from a statistically significant perspective. lots of people can lie with statistics, but to make good decisions you have to know how to evaluate data and separate the wheat from the chaff. and that includes a fundamental ability to understand trends, build valuable data collection into your projects and pay attention to things like sample size and cyclical considerations that can mislead.
billions of dollars are wasted upon conclusions built upon fallacy.
in the (meaningful) data, we can find absolute truth--it's black and white, unyielding and decisive.
and there's no better feeling than making decisions on that kind of stability.
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