Analyzing Us Census Data

Census data are widely used by practitioners to understand demographic change, allocate resources, address inequalities, and make sound business decisions. Until recently, projects using US Census data have required proficiency with multiple web interfaces and software platforms to prepare, map, and present data products. This book introduces readers to tools in the R programming language for accessing and analyzing Census data, helping analysts manage these types of projects in a single computing environment. Chapters in this book cover the following key topics: • Rapidly acquiring data from the decennial US Census and American Community Survey using R, then analyzing these datasets using tidyverse tools; • Visualizing US Census data with a wide range of methods including charts in ggplot2 as well as both static and interactive maps; • Using R as a geographic information system (GIS) to manage, analyze, and model spatial demographic data from the US Census; • Working with and modeling individual-level microdata from the American Community Survey’s PUMS datasets; • Applying these tools and workflows to the analysis of historical Census data, other US government datasets, and international Census data from countries like Canada, Brazil, Kenya, and Mexico. Kyle Walker is an associate professor of geography at Texas Christian University, director of TCU’s Center for Urban Studies, and a spatial data science consultant. His research focuses on demographic trends in the United States, demographic data visualization, and software tools for open spatial data science. He is the lead author of a number of R packages including tigris, tidycensus, and mapboxapi.

Exploring the U.S. Census gives social science students and researchers alike the tools to understand, extract, process, and analyze data from the decennial census, the American Community Survey, and other data collected by the U.S. Census Bureau. Donnelly′s text provides a thorough background on the data collection methods, structures, and potential pitfalls of the census for unfamiliar researchers, collecting information previously available only in widely disparate sources into one handy guide. Hands-on, applied exercises at the end of the chapters help readers dive into the data. Along the way, the author shows how best to analyze census data with open-source software and tools. Readers can freely evaluate the data on their own computers, in keeping with the free and open data provided by the Census Bureau. By placing the census in the context of the open data movement, this text makes the history and practice of the census relevant so readers can understand what a crucial resource the census is for research and knowledge.

The U.S. census, conducted every 10 years since 1790, faces dramatic new challenges as the country begins its third century. Critics of the 1990 census cited problems of increasingly high costs, continued racial differences in counting the population, and declining public confidence. This volume provides a major review of the traditional U.S. census. Starting from the most basic questions of how data are used and whether they are needed, the volume examines the data that future censuses should provide. It evaluates several radical proposals that have been made for changing the census, as well as other proposals for redesigning the year 2000 census. The book also considers in detail the much-criticized long form, the role of race and ethnic data, and the need for and ways to obtain small-area data between censuses.

How to parse, analyze, and incorporate census data This handy resource offers a reference guide for anyone interested in tailoring specific Census data to their needs. It includes computer coding (SAS v9.x) software for extracting targeted data from thousands of Census files, as well as primers on using online tools and mapping software for analyzing data. The book offers thorough coverage of all aspects of census data including its historical significance, suggestions for parsing housing, occupation, transportation, economic, health, and other data from the census, and much more. Offers an guide to analyzing Census data that can have an impact on financial markets as well as housing and economic data boding ill or well for the future of the economy It includes computer coding (SAS v9.x) scripts for extracting specific data from Census files Offers guidance on using thousands of variables from Census results released every year and American Community Survey data now released every year The only one-stop guide to analyzing and using annual and decennial Census data Bass offers a practical guide for leveraging information compiled by the Census to further research as well as business interests.

This book provides an up-to-date overview of demographic analysis and methods, including recent developments in demography. Concepts and methods, from the nature of demographic information through data collection and the basics of statistical measures and on to demographic analysis itself are succinctly explained. Measures and analyses of fertility, mortality, life tables, migration and demographic events such as marriage, education and labour force are described while later chapters cover multiple decrement tables, population projections, the importance of testing and smoothing demographic data, the stable population model and demographic software. An emphasis on practical aspects and the use of real-life examples based on data from around the globe make this book accessible, whilst comprehensive references and links to data and other resources on the internet help readers to explore further. The text is concise and well written, making it ideally suited to a wider audience from students to academics and teachers. Students of demography, geography, sociology, economics, as well as professionals, academics and students of marketing, human resource management, and public health who have an interest in population issues will all find this book useful.

Applied Spatial Data Analysis with R, second edition, is divided into two basic parts, the first presenting R packages, functions, classes and methods for handling spatial data. This part is of interest to users who need to access and visualise spatial data. Data import and export for many file formats for spatial data are covered in detail, as is the interface between R and the open source GRASS GIS and the handling of spatio-temporal data. The second part showcases more specialised kinds of spatial data analysis, including spatial point pattern analysis, interpolation and geostatistics, areal data analysis and disease mapping. The coverage of methods of spatial data analysis ranges from standard techniques to new developments, and the examples used are largely taken from the spatial statistics literature. All the examples can be run using R contributed packages available from the CRAN website, with code and additional data sets from the book's own website. Compared to the first edition, the second edition covers the more systematic approach towards handling spatial data in R, as well as a number of important and widely used CRAN packages that have appeared since the first edition. This book will be of interest to researchers who intend to use R to handle, visualise, and analyse spatial data. It will also be of interest to spatial data analysts who do not use R, but who are interested in practical aspects of implementing software for spatial data analysis. It is a suitable companion book for introductory spatial statistics courses and for applied methods courses in a wide range of subjects using spatial data, including human and physical geography, geographical information science and geoinformatics, the environmental sciences, ecology, public health and disease control, economics, public administration and political science. The book has a website where complete code examples, data sets, and other support material may be found: http://www.asdar-book.org. The authors have taken part in writing and maintaining software for spatial data handling and analysis with R in concert since 2003.

Census workers need to capture and analyze information at the finest geographic level with mobile and geospatial-based technology. GIS and the 2020 Census: Modernizing Official Statistics provides statistical organizations with the most recent GIS methodologies and technological tools to support census workers' needs at all the stages of a census. Learn how to plan and carry out census work with GIS using new technologies for field data collection and operations management. After planning and collecting data, apply innovative solutions for performing statistical analysis, data integration and dissemination. Additional topics cover cloud computing, big data, Location as a Service (LaaS), and emerging data sources. While GIS and the 2020 Census focuses on using GIS and other geospatial technology in support of census planning and operations, it also offers guidelines for building a statistical-geospatial information infrastructure in support of the 2020 Round of Censuses, evidence-based decision making, and sustainable development. Case studies illustrate concepts in practice.