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	Robust Chi-Square Test	फिशर का सटीक परीक्षण
क्षेत्र	सांख्यिकी	सांख्यिकी
परिवार	Hypothesis test	Hypothesis test
उद्भव वर्ष	1984 (power divergence); 1900 (Pearson baseline)	1922
प्रवर्तक	Cressie & Read (power divergence framework); Pearson chi-square extended by multiple authors	R. A. Fisher
प्रकार	Robust categorical association / goodness-of-fit test	Exact test of independence for categorical data
मौलिक स्रोत	Cressie, N., & Read, T. R. C. (1984). Multinomial goodness-of-fit tests. Journal of the Royal Statistical Society: Series B, 46(3), 440–464.	Fisher, R. A. (1922). On the interpretation of chi-squared from contingency tables, and the calculation of P. Journal of the Royal Statistical Society, 85(1), 87–94.
उपनाम	robust chi-squared test, Cressie-Read power divergence test, adjusted chi-square test, robust contingency test	Fisher-Irwin test, exact test of independence, Fisher'ın Kesin Testi
संबंधित	3	2
सारांश	The robust chi-square test extends the classic Pearson chi-square framework to remain reliable when standard assumptions — especially the minimum expected-cell-count rule — are violated. Using power divergence statistics (Cressie & Read, 1984) or resampling-based corrections, it produces valid inferences for sparse contingency tables, small samples, and unbalanced categorical data where the ordinary chi-square approximation breaks down.	Fisher's exact test is a nonparametric exact-probability test of independence for small-sample contingency tables, introduced by R. A. Fisher in 1922. Rather than relying on a large-sample approximation, it computes the exact probability of the observed table directly from the hypergeometric distribution.