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- W4245399891 abstract "This chapter describes the theory of point estimation. It shows how R can easily calculate estimates of location and scale parameters as well as higher moments from a data set. The most important scale parameters are the range, the interquartile range, and the standard deviation (except the variance). They all have the same dimensions as the observations. The sample range <i>R</i> is a function of the order statistics of the sample its realisation is the difference between the largest and the smallest value of the sample. Contingency tables are used when observations are nominally scaled. The chapter describes contingency tables in general, even if not only problems of estimation are handled by them. The models depend on how many factors are observed by the experimenter (they are observation factors) and thus contain random results. The other factors are called fixed factors. The chapter explains this by a two-dimensional contingency table." @default.
- W4245399891 created "2022-05-12" @default.
- W4245399891 date "2019-08-16" @default.
- W4245399891 modified "2023-09-27" @default.
- W4245399891 title "Point Estimation" @default.
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- W4245399891 doi "https://doi.org/10.1002/9781119551584.ch2" @default.
- W4245399891 hasPublicationYear "2019" @default.
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