On the Choice of the Number of Class Intervals in the Application of the Chi Square Test

By H. B. Mann, A. Wald. 1942

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Inference Under Information Constraints I: Lower Bounds From Chi-Square Contraction (2018, background): “[39]), with particular interest on the large-support and small-sample case where the usual normal approximations of statistics do not apply (cf.”
CORDS: automatic discovery of correlations and soft functional dependencies (2004, methodology): “We also restrict the discussion to the case of categorical or discrete-valued data—see [15] for a discussion of how to apply the chi-squared test to real-valued data.”
A Tale of Tails: An Empirical Analysis of Loss Distribution Models for Estimating Operational Risk Capital (2006, background): “Mann and Wald (1942) and Cohen and Sackrowitz (1975) proved that Pearson’s test statistic is unbiased when the cells are chosen to have equal probabilities under the null.”
A Bayesian chi^2 test for goodness-of-fit (2004, unknown): “, Moore and Spruill (1975), although emphasis there focuses on randomized cells rather than on posterior sampling of parameter vectors.”