Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Potential fitting biases resulting from grouping data into variable
  width bins   When reading peer-reviewed scientific literature describing any analysis of
empirical data, it is natural and correct to proceed with the underlying
assumption that experiments have made good faith efforts to ensure that their
analyses yield unbiased results. However, particle physics experiments are
expensive and time consuming to carry out, thus if an analysis has inherent
bias (even if unintentional), much money and effort can be wasted trying to
replicate or understand the results, particularly if the analysis is
fundamental to our understanding of the universe.
  In this note we discuss the significant biases that can result from data
binning schemes. As we will show, if data are binned such that they provide the
best comparison to a particular (but incorrect) model, the resulting model
parameter estimates when fitting to the binned data can be significantly
biased, leading us to too often accept the model hypothesis when it is not in
fact true. When using binned likelihood or least squares methods there is of
course no a priori requirement that data bin sizes need to be constant, but we
show that fitting to data grouped into variable width bins is particularly
prone to produce biased results if the bin boundaries are chosen to optimize
the comparison of the binned data to a wrong model. The degree of bias that can
be achieved simply with variable binning can be surprisingly large.
  Fitting the data with an unbinned likelihood method, when possible to do so,
is the best way for researchers to show their analyses are not biased by
binning effects. Failing that, equal bin widths should be employed as a
cross-check of the fitting analysis whenever possible.

22
The categories of this paper are: chao-dyn
33
The categories of this paper are: plasm-ph
27
The categories of this paper are: comp-gas
24
The categories of this paper are: dg-ga
1
The categories of this paper are: cs
32
The categories of this paper are: atom-ph
26
The categories of this paper are: bayes-an
35
The categories of this paper are: mtrl-th
34
The categories of this paper are: chem-ph
15
The categories of this paper are: nucl-ex
23
The categories of this paper are: solv-int
4
The categories of this paper are: cond-mat
18
The categories of this paper are: econ
37
The categories of this paper are: supr-con
0
The categories of this paper are: hep-ph
13
The categories of this paper are: quant-ph