The idea that you should 'plot the error bars' ahead of, well, looking at the data seems a bit premature. As many other comments have stated, looking at the dat

The idea that you should 'plot the error bars' ahead of, well, looking at the data seems a bit premature. As many other comments have stated, looking at the data first is critical. It drives me up the wall: we have 1200dpi printers, retina displays, and so on, and yet somehow people feel the need to collapse everything they've done to these giant finger-painting quality bar charts. Statistical tests are well and good, but I'm amazed at the extent to which smart people will happily plug data which they have never actually seen into statistical metrics. So a mean might be derived from 9 reasonable results and a howlingly off factor-of-2 outlier, and you can dutifully plug this series into a bunch of standard tests and speak confidently about p-values.