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An Introduction to Nonparametric Statistics

John Kolassa

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Description:Introduction to Nonparametric Statistics presents the theory and practice of non-parametric statistics with an emphasis on motivating principals. The course is a combination of traditional rank-based methods and more computationally-intensive topics like density estimation, kernel smoothers in regression, and robustness. Most of the techniques described in this book apply to data with only minimal restrictions placed on their probability distributions, but performance of these techniques, and the performance of analogous parametric procedures, depends on these probability distributions. Conceptual developments in this text are intended to be independent of the computational tools used in practice, but analyses used to illustrate techniques developed in this book will be facilitated using the program R.Key Features: Strong focus on foundational issuesFocus on both rank-based and more modern techniquesHomework problems based on real dataSupplemental tools for computation in both RThis book is intended to accompany a one-semester graduate-level course in nonparametric statistics.We have made it easy for you to find a PDF Ebooks without any digging. And by having access to our ebooks online or by storing it on your computer, you have convenient answers with An Introduction to Nonparametric Statistics. To get started finding An Introduction to Nonparametric Statistics, you are right to find our website which has a comprehensive collection of manuals listed.
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ISBN: 0429511361

Description: Introduction to Nonparametric Statistics presents the theory and practice of non-parametric statistics with an emphasis on motivating principals. The course is a combination of traditional rank-based methods and more computationally-intensive topics like density estimation, kernel smoothers in regression, and robustness. Most of the techniques described in this book apply to data with only minimal restrictions placed on their probability distributions, but performance of these techniques, and the performance of analogous parametric procedures, depends on these probability distributions. Conceptual developments in this text are intended to be independent of the computational tools used in practice, but analyses used to illustrate techniques developed in this book will be facilitated using the program R.Key Features: Strong focus on foundational issuesFocus on both rank-based and more modern techniquesHomework problems based on real dataSupplemental tools for computation in both RThis book is intended to accompany a one-semester graduate-level course in nonparametric statistics.We have made it easy for you to find a PDF Ebooks without any digging. And by having access to our ebooks online or by storing it on your computer, you have convenient answers with An Introduction to Nonparametric Statistics. To get started finding An Introduction to Nonparametric Statistics, you are right to find our website which has a comprehensive collection of manuals listed.
Our library is the biggest of these that have literally hundreds of thousands of different products represented.

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An Introduction to Nonparametric Statistics

An Introduction to Nonparametric Statistics

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