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R Companion for Sampling: Design and Analysis, Third Edition
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R Companion for Sampling: Design and Analysis, Third Edition Paperback - 2021

by Yan Lu; Sharon L. Lohr

From the publisher

The R Companion for Sampling: Design and Analysis, designed to be read alongside Sampling: Design and Analysis, Third Edition by Sharon L. Lohr (SDA; 2022, CRC Press), shows how to use functions in base R and contributed packages to perform calculations for the examples in SDA.

No prior experience with R is needed. Chapter 1 tells you how to obtain R and RStudio, introduces basic features of the R statistical software environment, and helps you get started with analyzing data.

Each subsequent chapter provides step-by-step guidance for working through the data examples in the corresponding chapter of SDA, with code, output, and interpretation. Tips and warnings help you develop good programming practices and avoid common survey data analysis errors.

R features and functions are introduced as they are needed so you can see how each type of sample is selected and analyzed. Each chapter builds on the knowledge developed earlier for simpler designs; after finishing the book, you will know how to use R to select and analyze almost any type of probability sample.

All R code and data sets used in this book are available online to help you develop your skills analyzing survey data from social and public opinion research, public health, crime, education, business, agriculture, and ecology.

Details

  • Title R Companion for Sampling: Design and Analysis, Third Edition
  • Author Yan Lu; Sharon L. Lohr
  • Binding Paperback
  • Pages 222
  • Volumes 1
  • Language ENG
  • Publisher CRC Press
  • Date 2021-11-25
  • Illustrated Yes
  • Features Bibliography, Illustrated, Index
  • ISBN 9781032135946 / 1032135948
  • Weight 0.87 lbs (0.39 kg)
  • Dimensions 10 x 7 x 0.47 in (25.40 x 17.78 x 1.19 cm)
  • Library of Congress subjects Sampling (Statistics), R (Computer program language)
  • Library of Congress Catalog Number 2021039318
  • Dewey Decimal Code 519.520

About the author

Yan Lu is Associate Professor of Statistics at the University of New Mexico. Her research interests include survey sampling, mixed models, nonparametric regression, and data mining. Recent publications develop new statistical methods for combining data from multiple surveys, selecting probability samples from massive data streams, and applying nonparametric regression to survey data.

Sharon L. Lohr, the author of Measuring Crime: Behind the Statistics, has published widely about survey sampling and statistical methods for education, public policy, law, and crime. She is a Fellow of the American Statistical Association and an elected member of the International Statistical Institute, and has received the Gertrude M. Cox, Morris Hansen, and Deming Awards. Formerly Dean's Distinguished Professor of Statistics at Arizona State University and a Vice President at Westat, she is now a statistical consultant and writer.

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R Companion for Sampling: Design and Analysis, Third Edition
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New. The R Companion for Sampling: Design and Analysis, designed to be read alongside Sampling: Design and Analysis, Third Edition by Sharon L. Lohr (SDA; 2022, CRC Press), shows how to use functions in base R and contributed packages to perform calculations for the examples in SDA. No prior experience with R is needed. Chapter 1 tells you how to obtain R and RStudio, introduces basic features of the R statistical software environment, and helps you get started with analyzing data. Each subsequent chapter provides step-by-step guidance for working through the data examples in the corresponding chapter of SDA, with code, output, and interpretation. Tips and warnings help you develop good programming practices and avoid common survey data analysis errors. R features and functions are introduced as they are needed so you can see how each type of sample is selected and analyzed. Each chapter builds on the knowledge developed earlier for simpler designs; after finishing the book, you will know how… Read More
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