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I have an experiment in which I take an image of a flame. I then run a software routine that tells me what the concentrations of OH (hydroxyl) is at different heights above the flame. I first have to give it a calibrated image of a flame with known data and it then is able to give me data about an unknown flame as stated above. Here is what I have done:

1. Give calibrated the software with a known flame image with known data

2. Imaged 2 different flames that are unknown. the software then returns the OH concentrations of these tow flames.

I am curious to know what statistical measures are important? I suppose I should compare the 2 data sets from the unknown flames so I can show that the data sets are statistically similar and not outside of the bounds of experimental error.

Any thoughts? Please let me know if you need more information.

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# Comparing Results from an Experiment: What Statistical Measure is Important?

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