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| Author | : Alan H. Peters |
| Publisher | : Esri Press |
| Total Pages | : 342 |
| Release | : 2004 |
| Genre | : Political Science |
| ISBN | : |
Seeking to demystify the census and explaining the potential of GIS for understanding people, places, and local economies, this guide explains how geographic information systems (GIS) can significantly ease data management, allowing for new ways to analyze and present relationships among variables.
| Author | : Kyle Walker |
| Publisher | : CRC Press |
| Total Pages | : 0 |
| Release | : 2022-11 |
| Genre | : Business & Economics |
| ISBN | : 9780203711415 |
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 the book cover 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 analysis of historical Census data, other US government datasets, and international Census data from countries like Canada, Brazil, Kenya, and Mexico.
| Author | : Francis P. Donnelly |
| Publisher | : SAGE Publications |
| Total Pages | : 465 |
| Release | : 2019-10-07 |
| Genre | : Computers |
| ISBN | : 1544355459 |
Exploring the U.S. Census gives social science students and researchers the tools to understand, extract, process, and analyze census data, including the American Community Survey and other datasets. This text provides background on the data collection methods, structures, and potential pitfalls for unfamiliar researchers with applied exercises and software walk-throughs.
| Author | : William P. O’Hare |
| Publisher | : Springer |
| Total Pages | : 174 |
| Release | : 2019-02-13 |
| Genre | : Social Science |
| ISBN | : 3030109739 |
This open access book describes the differences in US census coverage, also referred to as “differential undercount”, by showing which groups have the highest net undercounts and which groups have the greatest undercount differentials, and discusses why such undercounts occur. In addition to focusing on measuring census coverage for several demographic characteristics, including age, gender, race, Hispanic origin status, and tenure, it also considers several of the main hard-to-count populations, such as immigrants, the homeless, the LBGT community, children in foster care, and the disabled. However, given the dearth of accurate undercount data for these groups, they are covered less comprehensively than those demographic groups for which there is reliable undercount data from the Census Bureau. This book is of interest to demographers, statisticians, survey methodologists, and all those interested in census coverage.
| Author | : Kyle Walker |
| Publisher | : CRC Press |
| Total Pages | : 378 |
| Release | : 2023-02-09 |
| Genre | : Business & Economics |
| ISBN | : 1351360302 |
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.
| Author | : Heather Isabella MacDonald |
| Publisher | : ESRI Press |
| Total Pages | : 0 |
| Release | : 2011 |
| Genre | : American community survey |
| ISBN | : 9781589482227 |
Urban Policy and the Census helps researchers and policy analysts gain an integrated understanding of census data and other relevant policy data sources, their strengths and limitations, and how best to use this data in policy research. Researchers will be able to critically assess decennial census and the American Community Survey data, which can be the starting point for spatial analysis for realistic policy planning and decision-making. The book shows that evidence-based policy is effective only when the evidence is sound and used appropriately. It provides guidance for analyzing demographic and social trends, economic trends, housing circumstances, and transportation issues.
| Author | : National Research Council |
| Publisher | : National Academies Press |
| Total Pages | : 301 |
| Release | : 1988-02-01 |
| Genre | : Science |
| ISBN | : 0309037492 |
This volume explores the scientific frontiers and leading edges of research across the fields of anthropology, economics, political science, psychology, sociology, history, business, education, geography, law, and psychiatry, as well as the newer, more specialized areas of artificial intelligence, child development, cognitive science, communications, demography, linguistics, and management and decision science. It includes recommendations concerning new resources, facilities, and programs that may be needed over the next several years to ensure rapid progress and provide a high level of returns to basic research.
| Author | : James V. Spickard |
| Publisher | : SAGE Publications |
| Total Pages | : 610 |
| Release | : 2016-09-15 |
| Genre | : Social Science |
| ISBN | : 1483387232 |
Research Basics: Design to Data Analysis in Six Steps offers a fresh and creative approach to the research process based on author James V. Spickard’s decades of teaching experience. Using an intuitive six-step model, readers learn how to craft a research question and then identify a logical process for answering it. Conversational writing and multi-disciplinary examples illuminate the model’s simplicity and power, effectively connecting the “hows” and “whys” behind social science research. Students using this book will learn how to turn their research questions into results.
| Author | : Roger S. Bivand |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 414 |
| Release | : 2013-06-21 |
| Genre | : Medical |
| ISBN | : 1461476186 |
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.
| Author | : Lex Comber |
| Publisher | : SAGE |
| Total Pages | : 460 |
| Release | : 2020-12-02 |
| Genre | : Science |
| ISBN | : 1526485435 |
We are in an age of big data where all of our everyday interactions and transactions generate data. Much of this data is spatial – it is collected some-where – and identifying analytical insight from trends and patterns in these increasing rich digital footprints presents a number of challenges. Whilst other books describe different flavours of Data Analytics in R and other programming languages, there are none that consider Spatial Data (i.e. the location attached to data), or that consider issues of inference, linking Big Data, Geography, GIS, Mapping and Spatial Analytics. This is a ‘learning by doing’ textbook, building on the previous book by the same authors, An Introduction to R for Spatial Analysis and Mapping. It details the theoretical issues in analyses of Big Spatial Data and developing practical skills in the reader for addressing these with confidence.
