An Introduction to Nonparametric Statistics + nemokamas atvežimas! | knygos.lt

Aprašymas

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 issues



Focus on both rank-based and more modern techniques



Homework problems based on real data



Supplemental tools for computation in both R

This book is intended to accompany a one-semester graduate-level course in nonparametric statistics.