Sampling consists of selection, acquisition, and quantification of a part of the population. While selection and acquisition apply to physical sampling units of the population, quantification pertains only to the variable of interest, which is a particular characteristic of the sampling units. A sampling procedure is expected to provide a sample that is representative with respect to some specified criteria. Composite sampling, under idealized conditions, incurs no loss of information for estimating the population means. But an important limitation to the method has been the loss of information on individual sample values, such as, the extremely large value. In many of the situations where individual sample values are of interest or concern, composite sampling methods can be suitably modified to retrieve the information on individual sample values that may be lost due to compositing. This book presents statistical solutions to issues that arise in the context of applications of composite sampling.
Statistics Using R will be useful at different levels, from an undergraduate course in statistics, through graduate courses in biological sciences, engineering, management and so on. The book introduces statistical terminology and defines it for the benefit of a novice. For a practicing statistician, it will serve as a guide to R language for statistical analysis. For a researcher, it is a dual guide, simultaneously explaining appropriate statistical methods for the problems at hand and indicating how these methods can be implemented using the R language. For a software developer, it is a guide in a variety of statistical methods for development of a suite of statistical procedures.
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