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In statistics, quality assurance, and survey methodology, sampling is the selection of a subset or a statistical sample (termed sample for short) of individuals from within a statistical population to estimate characteristics of the whole population.
This book offers a combination of an introduction to basic sampling theory, engaging presentation of topics that reflect current research trends, and informed discussion of the problems commonly encountered in survey practice. It integrates R packages for easy application of theory.
Sampling is a fundamental concept in statistics that involves selecting a subset of individuals from a larger population to draw conclusions. When done correctly, sampling can provide accurate insights while being cost-effective and time-efficient.
27 Απρ 2023 · If probability theory is the foundations upon which all statistical theory builds, sampling theory is the frame around which you can build the rest of the house. Sampling theory plays a huge role in specifying the assumptions upon which your statistical inferences rely.
The aim of this course is to cover sampling design and analysis methods that would be useful for research and management in many field. A well designed sampling procedure ensures that we can summarize and analyze data with a minimum of assumptions and complications.
The papers highlight state-of-the-art advances and trends in sampling theory and related areas of application, such as signal and image processing. Chapters have been written by prominent mathematicians, applied scientists, and engineers with an expertise in sampling theory.
Sampling is a statistical methodology that uses a portion of a total population to represent the full population. As a subject, sampling considers the different methodologies one could use to survey a portion of the population and seeks to find a sample that is most indicative of the overall population.
