Kate Storey-Fisher (NYU) and I discussed various things, but one of the important points of her project relates to the properties of histograms. My loyal reader knows that she is replacing the usual two-point correlation function estimator for large-scale structure surveys with one that does not require that the galaxy pairs be put into bins by radial separation. One of the main points of the method is that it permits continuous-function bases that are better at expressing expected correlation functions than the usual binned estimators, which are like histograms. We are trying to visualize these points in the paper, showing that as you go to larger bins, the usual binned estimator becomes more precise (lower variance) but less accurate (more bias) and vice versa. I also (a week or so ago) demonstrated this for just normal histograms in this notebook.
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