Item Details
ChiSquared Goodness of Fit Tests With Applications [electronic resource]
V. Voinov, KIMEP University; Institute for Mathematics and Mathematical Modeling of the Ministry of Education and Science, Almaty, Kazakhstan, M. Nikulin, University Bordeaux2, Bordeaux, France, N. Balakrishnan, McMaster University, Hamilton, Ontario, Canada
 Format
 EBook; Book; Online
 Published
 Amsterdam : Elsevier/AP, [2013]
 Language
 English
 ISBN
 9780123971944 (hardback)
 Summary
 "If the number of sample observations n ! 1, the statistic in (1.1) will follow the chisquared probability distribution with r1 degrees of freedom. We know that this remarkable result is true only for a simple null hypothesis when a hypothetical distribution is specified uniquely (i.e., the parameter is considered to be known). Until 1934, Pearson believed that the limiting distribution of the statistic in (1.1) will be the same if the unknown parameters of the null hypothesis are replaced by their estimates based on a sample; see, for example, Baird (1983), Plackett (1983, p. 63), Lindley (1996), Rao (2002), and Stigler (2008, p. 266). In this regard, it is important to reproduce the words of Plackett (1983, p. 69) concerning E. S. Pearson's opinion: "I knew long ago that KP (meaning Karl Pearson) used the 'correct' degrees of freedom for (a) difference between two samples and (b) multiple contingency tables. But he could not see that
 Description
 Mode of access: World wide Web.
 Notes
 Includes bibliographical references (pages 215226) and index.
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LEADER 03048cam a2200373 i 4500001 u6154966003 SIRSI005 20150708061627.0006 m d007 cr n008 121231s2013 ne a sb 001 0 eng da 2012039862a 9780123971944 (hardback)a (WaSeSS)ssj0000832877a DLC b eng c DLC d DLC d WaSeSSa pcca QA277.3 b .V65 2013a 519.5/6 2 23a Voinov, Vassiliy.a Chisquared goodness of fit tests with applications h [electronic resource] / c V. Voinov, KIMEP University; Institute for Mathematics and Mathematical Modeling of the Ministry of Education and Science, Almaty, Kazakhstan, M. Nikulin, University Bordeaux2, Bordeaux, France, N. Balakrishnan, McMaster University, Hamilton, Ontario, Canada.a Amsterdam : b Elsevier/AP, c [2013]a Includes bibliographical references (pages 215226) and index.a "If the number of sample observations n ! 1, the statistic in (1.1) will follow the chisquared probability distribution with r1 degrees of freedom. We know that this remarkable result is true only for a simple null hypothesis when a hypothetical distribution is specified uniquely (i.e., the parameter is considered to be known). Until 1934, Pearson believed that the limiting distribution of the statistic in (1.1) will be the same if the unknown parameters of the null hypothesis are replaced by their estimates based on a sample; see, for example, Baird (1983), Plackett (1983, p. 63), Lindley (1996), Rao (2002), and Stigler (2008, p. 266). In this regard, it is important to reproduce the words of Plackett (1983, p. 69) concerning E. S. Pearson's opinion: "I knew long ago that KP (meaning Karl Pearson) used the 'correct' degrees of freedom for (a) difference between two samples and (b) multiple contingency tables. But he could not see that 2 in curve fitting should be got asymptotically into the same category." Plackett explained that this crucial mistake of Pearson arose from to Karl Pearson's assumption "that individual normality implies joint normality." Stigler (2008) noted that this error of Pearson "has left a positive and lasting negative impression upon the statistical world." Fisher (1924) clearly showed 1 2 CHAPTER 1. A HISTORICAL ACCOUNT that the number of degrees of freedom of Pearson's test must be reduced by the number of parameters estimated from the sample" c Provided by publisher.a Mode of access: World wide Web.a Chisquare test.a Distribution (Probability theory)a Electronic books.a Balakrishnan, N., d 1956a Nikulin, M. S. q (Mikhail Stepanovich)a eBook  Mathematics 2013 [EBCM13]a Safari Books Onlineu http://RE5QY4SB7X.search.serialssolutions.com/?V=1.0&L=RE5QY4SB7X&S=JCs&C=TC0000832877&T=marca 1a XX(6154966.1) w WEB i 61549661001 l INTERNET m UVALIB t INTERNET