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Presents the survey methodologies of area and multiple frame agricultural survey programs currently used in a wide range of countries.
Due to the widespread use of surveys in agricultural resources estimation there is a broad and recognizable interest in methods and techniques to collect and process agricultural data. This book brings together the knowledge of academics and experts to increase the dissemination of the latest developments in agricultural statistics. Conducting a census, setting up frames and registers and using administrative data for statistical purposes are covered and issues arising from sample design and estimation, use of remote sensing, management of data quality and dissemination and analysis of survey data are explored. Key features: Brings together high quality research on agricultural statistics from experts in this field. Provides a thorough and much needed overview of developments within agricultural statistics. Contains summaries for each chapter, providing a valuable reference framework for those new to the field. Based upon a selection of key methodological papers presented at the ICAS conference series, updated and expanded to address current issues. Covers traditional statistical methodologies including sampling and weighting. This book provides a much needed guide to conducting surveys of land use and to the latest developments in agricultural statistics. Statisticians interested in agricultural statistics, agricultural statisticians in national statistics offices and statisticians and researchers using survey methodology will benefit from this book.
Extract: Multiple-frame surveys are susceptible to errors that stem from associating the over-lapping portions of the frames. Decreasing sampling error may improve precision, but it offers greater complications; nonsampling error would increase, leading to decreased accuracy and, perhaps, greater total error. This manuscript offers several procedures to improve consistency and accuracy of multiple-frame estimating by reducing nonsampling errors. Such procedures, when added to an optimum mix of sampling frames, would provide survey indications of greater reliability without increasing costs appreciably.
The research and its outcomes presented here focus on spatial sampling of agricultural resources. The authors introduce sampling designs and methods for producing accurate estimates of crop production for harvests across different regions and countries. With the help of real and simulated examples performed with the open-source software R, readers will learn about the different phases of spatial data collection. The agricultural data analyzed in this book help policymakers and market stakeholders to monitor the production of agricultural goods and its effects on environment and food safety.
This new handbook contains the most comprehensive account of sample surveys theory and practice to date. It is a second volume on sample surveys, with the goal of updating and extending the sampling volume published as volume 6 of the Handbook of Statistics in 1988. The present handbook is divided into two volumes (29A and 29B), with a total of 41 chapters, covering current developments in almost every aspect of sample surveys, with references to important contributions and available software. It can serve as a self contained guide to researchers and practitioners, with appropriate balance between theory and real life applications. Each of the two volumes is divided into three parts, with each part preceded by an introduction, summarizing the main developments in the areas covered in that part. Volume 29A deals with methods of sample selection and data processing, with the later including editing and imputation, handling of outliers and measurement errors, and methods of disclosure control. The volume contains also a large variety of applications in specialized areas such as household and business surveys, marketing research, opinion polls and censuses. Volume 29B is concerned with inference, distinguishing between design-based and model-based methods and focusing on specific problems such as small area estimation, analysis of longitudinal data, categorical data analysis and inference on distribution functions. The volume contains also chapters dealing with case-control studies, asymptotic properties of estimators and decision theoretic aspects. - Comprehensive account of recent developments in sample survey theory and practice - Discusses a wide variety of diverse applications - Comprehensive bibliography
Explore the classic and cutting-edge quantitative methods for understanding environmental science research Based on the multifaceted 16-volume Encyclopedia of Statistical Sciences, Second Edition, Methods and Applications of Statistics in the Atmospheric and Earth Sciences offers guidance on the application of statistical methods for conducting research in these fields of study. With contributions from more than 100 leading experts in academia and industry, this volume combines key articles from the Encyclopedia with newly developed topics addressing some of the more critical issues, including pollution, droughts, and volcanic activity. Readers will gain a thorough understanding of cutting-edge methods for the acquisition and analysis of data across a wide range of subject areas, from geophysics, geology, and biogeography to meteorology, forestry, agriculture, animal science, and ornithology. The book features new and updated content on quantitative methods and their use in understanding the latest topics in social research, including: Drought Analysis and Forecasting Childhood Obesity Ranked Set Sampling Methodology for Environmental Data Species Richness and Shared Species Richness Geographic Information Systems Each contribution offers authoritative yet easily accessible coverage of statistical concepts. With updated references and discussion of emerging topics, readers are provided with the various statistical methods, techniques, strategies, and applications that are essential for tackling critical issues in environmental science research. Featuring a balance of classical and cutting-edge methodologies, Methods and Applications of Statistics in the Atmospheric and Earth Sciences is an excellent resource for researchers, professionals, and students in the fields of sociology, psychology, philosophy, education, political science, and the related disciplines who would like to learn about the uses of statistics in gathering, reporting, and analyzing data.
As a member of the working group on data disaggregation, the Food and Agriculture Organization of the United Nations (FAO) has taken numerous steps towards supporting Member Countries in the production of disaggregated estimates. Within this framework, these Guidelines offer methodological and practical guidance for the production of direct and indirect disaggregated estimates of SDG indicators having surveys as their main or preferred data source. Furthermore, the publication provides tools to assess the accuracy of these estimates and presents strategies for the improvement of output quality, including Small Area Estimation methods.