Hot takes on data analysis
Some short, hot takes on data analysis.
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Measuring experiment success is a hard problem.
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Failed experiments are the value of experimentation.
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Make decisions with scalar parameters.
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Complex models need an explanation of exactly what data they use to answer a question. Black boxes are bad.
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Numerical optimization is a hard problem not an afterthought.
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The weaker the theory, the more robust the results. The stronger the theory, the more meaningful the results.
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| Hot Take |
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[Click links to insert hot takes.]
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