(c) The ultimate calculation of the energy resolution: Fit your data to a function that represents the measured gamma ray spectrum. For the voltage bins near the gamma ray the spectrum can be thought to consist of two components, the gamma ray itself (our signal), which we can model with a Gaussian, and background. If there were no background then the estimated number of counts in bin i would be : Here xi is either the voltage or energy. We would like to determine the constants A, , and s that best describe our data. Unfortunately, we also have background in our spectrum. Let's assume that , the number of background count in bin i, in the area of interest can be modeled by a straight line (is this reasonable?): Again, the constants C and D are to be determined from our data. Now, since our data really consists of background and signal the best representation of our data is given by the sum of the signal and background functions: The problem now is to determine the 5 constants (A, C, D, , s) from our data points. In principle this is simple, we use a technique such as Maximum Likelihood or Least Squares to find the 5 parameters. In practice this is difficult since the above function is non-linear in some of the variables, thus we would have to solve a set of 5 coupled non-linear equations! So we will use LabPlot2 to fit the data with the complicated functions. You should weigh each data point using its statistical error and make sure that each statistical error is included (