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Chi-Square Distribution: New Derivations and Environmental Application
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作者 Thomas M. Semkow nicole freeman +8 位作者 Umme-Farzana Syed Douglas K. Haines Abdul Bari Abdul J. Khan Kimi Nishikawa Adil Khan Adam G. Burn Xin Li Liang T. Chu 《Journal of Applied Mathematics and Physics》 2019年第8期1786-1799,共14页
We describe two new derivations of the chi-square distribution. The first derivation uses the induction method, which requires only a single integral to calculate. The second derivation uses the Laplace transform and ... We describe two new derivations of the chi-square distribution. The first derivation uses the induction method, which requires only a single integral to calculate. The second derivation uses the Laplace transform and requires minimum assumptions. The new derivations are compared with the established derivations, such as by convolution, moment generating function, and Bayesian inference. The chi-square testing has seen many applications to physics and other fields. We describe a unique version of the chi-square test where both the variance and location are tested, which is then applied to environmental data. The chi-square test is used to make a judgment whether a laboratory method is capable of detection of gross alpha and beta radioactivity in drinking water for regulatory monitoring to protect health of population. A case of a failure of the chi-square test and its amelioration are described. The chi-square test is compared to and supplemented by the t-test. 展开更多
关键词 Mathematical Induction LAPLACE Transform GAMMA Distribution CHI-SQUARE Test GROSS Alpha-Beta DRINKING Water
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