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Distance sampling is a widely used group of closely related methods for estimating the density and/or abundance of populations. ... Data example All animals on the ...
Line plot survey is a systematic sampling technique used on land surfaces for laying out sample plots within a rectangular grid to conduct forest inventory or agricultural research. It is a specific type of systematic sampling, similar to other statistical sampling methods such as random sampling, but more straightforward to carry out in ...
Method Utility Branches Distance sampling: Used for estimating the density and/or abundance of populations: Ecology: Mark and recapture: Used to estimate an animal population's size where it is impractical to count every individual. [17] Ecology
In ecology, plot sampling is a widely used method of abundance estimation in which specific areas, or plots, are selected from within a survey region and sampled. This approach allows scientists to make population estimates using statistical techniques such as the Horvitz–Thompson estimator .
Mark and recapture is a method commonly used in ecology to estimate an animal population's size where it is impractical to count every individual. [1] A portion of the population is captured, marked, and released. Later, another portion will be captured and the number of marked individuals within the sample is counted.
In statistics, probability theory, and information theory, a statistical distance quantifies the distance between two statistical objects, which can be two random variables, or two probability distributions or samples, or the distance can be between an individual sample point and a population or a wider sample of points. A distance between ...
A visual representation of the sampling process. 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 jackknife pre-dates other common resampling methods such as the bootstrap. Given a sample of size n {\displaystyle n} , a jackknife estimator can be built by aggregating the parameter estimates from each subsample of size ( n − 1 ) {\displaystyle (n-1)} obtained by omitting one observation.