Sharon L. Lohr – författare

Much of the statistical information currently produced by federal statistical agencies - information about economic, social, and physical well-being that is essential for the functioning of modern society - comes from sample surveys. In recent years, there has been a proliferation of data from other sources, including data collected by government agencies while administering programs, satellite and sensor data, private-sector data such as electronic health records and credit card transaction data, and massive amounts of data available on the internet. How can these data sources be used to enhance the information currently collected on surveys, and to provide new frontiers for producing information and statistics to benefit American society?

Toward a 21st Century National Data Infrastructure: Enhancing Survey Programs by Using Multiple Data Sources, the second report in a series funded by the National Science Foundation, discusses how use of multiple data sources can improve the quality of national and subnational statistics while promoting data equity. This report explores implications of combining survey data with other data sources through examples relating to the areas of income, health, crime, and agriculture.

"The level is appropriate for an upper-level undergraduate or graduate-level statistics major. Sampling: Design and Analysis (SDA) will also benefit a non-statistics major with a desire to understand the concepts of sampling from a finite population. A student with patience to delve into the rigor of survey statistics will gain even more from the content that SDA offers. The updates to SDA have potential to enrich traditional survey sampling classes at both the undergraduate and graduate levels. The new discussions of low response rates, non-probability surveys, and internet as a data collection mode hold particular value, as these statistical issues have become increasingly important in survey practice in recent years… I would eagerly adopt the new edition of SDA as the required textbook." (Emily Berg, Iowa State University)

What is the unemployment rate? What is the total area of land planted with soybeans? How many persons have antibodies to the virus causing COVID-19? Sampling: Design and Analysis, Third Edition shows you how to design and analyze surveys to answer these and other questions. This authoritative text, used as a standard reference by numerous survey organizations, teaches the principles of sampling with examples from social sciences, public opinion research, public health, business, agriculture, and ecology. Readers should be familiar with concepts from an introductory statistics class including probability and linear regression; optional sections contain statistical theory for readers familiar with mathematical statistics.

Key Features:

SDA’s companion website contains data sets, computer code, and links to two free downloadable supplementary books (also available in paperback) that provide step-by-step guides—with code, annotated output, and helpful tips—for working through the SDA examples. Instructors can use either R or SAS® software.

"The level is appropriate for an upper-level undergraduate or graduate-level statistics major. Sampling: Design and Analysis (SDA) will also benefit a non-statistics major with a desire to understand the concepts of sampling from a finite population. A student with patience to delve into the rigor of survey statistics will gain even more from the content that SDA offers. The updates to SDA have potential to enrich traditional survey sampling classes at both the undergraduate and graduate levels. The new discussions of low response rates, non-probability surveys, and internet as a data collection mode hold particular value, as these statistical issues have become increasingly important in survey practice in recent years… I would eagerly adopt the new edition of SDA as the required textbook." (Emily Berg, Iowa State University)

What is the unemployment rate? What is the total area of land planted with soybeans? How many persons have antibodies to the virus causing COVID-19? Sampling: Design and Analysis, Third Edition shows you how to design and analyze surveys to answer these and other questions. This authoritative text, used as a standard reference by numerous survey organizations, teaches the principles of sampling with examples from social sciences, public opinion research, public health, business, agriculture, and ecology. Readers should be familiar with concepts from an introductory statistics class including probability and linear regression; optional sections contain statistical theory for readers familiar with mathematical statistics.

Key Features:

SDA’s companion website contains data sets, computer code, and links to two free downloadable supplementary books (also available in paperback) that provide step-by-step guides—with code, annotated output, and helpful tips—for working through the SDA examples. Instructors can use either R or SAS® software.

The SAS® Software 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 the survey selection and analysis procedures of SAS® software to perform calculations for the examples in SDA.

No prior experience with SAS software is needed. Chapter 1 tells you how to access the software, introduces basic features, 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.

Features of the SAS software procedures 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 SAS software to select and analyze almost any type of probability sample.

All code is available on the book website and is easily adapted for your own survey data analyses. The website also contains all data sets from the examples and exercises in SDA to help you develop your skills through analyzing survey data from social and public opinion research, public health, crime, education, business, agriculture, and ecology

The SAS® Software 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 the survey selection and analysis procedures of SAS® software to perform calculations for the examples in SDA.

No prior experience with SAS software is needed. Chapter 1 tells you how to access the software, introduces basic features, 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.

Features of the SAS software procedures 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 SAS software to select and analyze almost any type of probability sample.

All code is available on the book website and is easily adapted for your own survey data analyses. The website also contains all data sets from the examples and exercises in SDA to help you develop your skills through analyzing survey data from social and public opinion research, public health, crime, education, business, agriculture, and ecology

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.

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.