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Define the most important parameters for your sampling, such as age, height, health, etc. Divide the trees into bins. Determine the percentage of trees in each bin. Choose a percentage of trees from each bin to sample. Using those numbers, choose random samples from within each bin.
Probability sampling methods include simple random sampling, systematic sampling, stratified sampling, and cluster sampling.
There are five types of sampling: Random, Systematic, Convenience, Cluster, and Stratified. Random sampling is analogous to putting everyones name into a hat and drawing out several names. Each element in the population has an equal chance of occuring.
Stream sampling is the process of collecting a representative sample of the elements of a data stream. The sample is usually much smaller than the entire stream, but can be designed to retain many important characteristics of the stream, and can be used to estimate many important aggregates on the stream.
Plant sampling methods include transects, quadrats, and aerial observations. Transects measure vegetation variation along a line, showing how plant communities change with the environment. Quadrats quantify plant coverage and abundance within a grid.
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Foresters use two primary methods: sample plots and a 100% tally (counting every tree). Sampling is the usual method, because counting and measuring every tree in an 80-acre forest or even an 8-acre forest would be time-consuming, prohibitively expensive, and (usually) statistically unnecessary.

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