Hello, I'm attempting to analyse the data recovered from an experiment that I performed in lab, but I'm having some problems understanding how to properly apply the statistical methods learned to this specific problem.(adsbygoogle = window.adsbygoogle || []).push({});

Essentially, the experiment consisted of placing a source of gamma rays near to a detector and counting the number of photons detected in an interval of 2 minutes. We then placed increasing thicknesses of a given material and observed how the number of photons counted (in 2 minutes) was affected.

As such I have a table of values of width versus number of counts. Due to time constraints, we could only perform the experiment twice, so for each thickness, I have two values for the number of photons counted. I figured that I could take the average of these values and the standard deviation and use that to plot a curve with error bars. The problem is that two of the values have exactly the same number of counts (this seemed insanely unlikely given that the number of counts was on the order of 500 and the other values for standard deviation are around 30/40), so for these 2 widths, I have a standard deviation of zero.

Looking at the curve, it seemed apparent that an exponential curve would be a good fit, so that is what I am attempting to do. However, my curve fitting program is throwing up massive problems due to the two values with "zero" error. I anticipate the error to increase with the number of counts, so I can't just set a constant error value. So my trouble is how to resolve in a sound manner these crazy zero errors that I'm finding. Any help would be enormously useful because I'm at an utter loss as to what to do here!

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# Data Analysis: Gamma ray attenuation

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