Although experiments and data are crucial to the fields of science and engineering, scientists and engineers also know experiments and data are messy. The number of ways data collection can fail – people forget to turn on the right switch at the right time, insects fly into critical components of an experiment, broken instruments, etc. – are myriad. Data-analysis routines then need to handle the cases of missing or bad data.
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