Survey sampling in the context of "Sample (statistics)"

⭐ In the context of statistics, survey sampling is considered a valuable technique primarily because it…

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⭐ Core Definition: Survey sampling

In statistics, survey sampling describes the process of selecting a sample of elements from a target population to conduct a survey. The term "survey" may refer to many different types or techniques of observation. In survey sampling it most often involves a questionnaire used to measure the characteristics and/or attitudes of people. Different ways of contacting members of a sample once they have been selected is the subject of survey data collection. The purpose of sampling is to reduce the cost and/or the amount of work that it would take to survey the entire target population. A survey that measures the entire target population is called a census. A sample refers to a group or section of a population from which information is to be obtained.

Survey samples can be broadly divided into two types: probability samples and super samples. Probability-based samples implement a sampling plan with specified probabilities (perhaps adapted probabilities specified by an adaptive procedure). Probability-based sampling allows design-based inference about the target population. The inferences are based on a known objective probability distribution that was specified in the study protocol. Inferences from probability-based surveys may still suffer from many types of bias.

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πŸ‘‰ Survey sampling in the context of Sample (statistics)

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. The subset is meant to reflect the whole population, and statisticians attempt to collect samples that are representative of the population. Sampling has lower costs and faster data collection compared to recording data from the entire population (in many cases, collecting the whole population is impossible, like getting sizes of all stars in the universe), and thus, it can provide insights in cases where it is infeasible to measure an entire population.

Each observation measures one or more properties (such as weight, location, colour or mass) of independent objects or individuals. In survey sampling, weights can be applied to the data to adjust for the sample design, particularly in stratified sampling. Results from probability theory and statistical theory are employed to guide the practice. In business and medical research, sampling is widely used for gathering information about a population. Acceptance sampling is used to determine if a production lot of material meets the governing specifications.

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Survey sampling in the context of Psychometrics

Psychometrics is a field of study within psychology concerned with the theory and technique of measurement. Psychometrics generally covers specialized fields within psychology and education devoted to testing, measurement, assessment, and related activities. Psychometrics is concerned with the objective measurement of latent constructs that cannot be directly observed. Examples of latent constructs include intelligence, personality factors (e.g., introversion), mental disorders, and educational achievement. The levels of individuals on nonobservable latent variables are inferred through mathematical modeling based on what is observed from individuals' responses to items on tests and scales.

Practitioners are described as psychometricians, although not all who engage in psychometric research go by this title. Most psychometricians are psychologists with advanced graduate training in psychometrics and measurement theory. According to the Dictionary of Psychology a psychometrician "is an individual with a theoretical knowledge of measurement techniques who is qualified to develop, evaluate, and improve psychological tests." In addition to traditional academic institutions, psychometricians also work for organizations, such as Pearson and the Educational Testing Service as well as independent consultants. Some psychometric researchers focus on the construction and validation of assessment instruments, including surveys, scales, and open- or close-ended questionnaires. Others focus on research relating to measurement theory (e.g., item response theory, intraclass correlation) or specialize as learning and development professionals.

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Survey sampling in the context of Randomized experiment

In science, randomized experiments are the experiments that allow the greatest reliability and validity of statistical estimates of treatment effects. Randomization-based inference is especially important in experimental design and in survey sampling.

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