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This page is the general description of the course and suggested expectations for both the student and the expectations of the teacher.

Sampling Probability Proportional to Prediction (PPP)

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Sampling Probability Proportional to Prediction is a method of sampling the depends on an expert estimator's ability to consistently estimate a particular value. In sampling physical values, tree diameter, fish length, bird weight, we are estimating the mean and variance of the actual measurement. In all of sampling, if you can reduce the variance you can reduce the sampling effort.

In this method, we no longer sample the actual physical measurement but the estimator's ability to estimate the physical measurement. In most cases for trained estimators there is less variance between the estimate and the actual value than in the original values. This method has several strong assumptions that must be met for the method to work well.

Assumptions:

1. Estimator must be consistent. Over or under estimates are not important but the relative values must be consistent.
2. To avoid bias the estimator must not know before the estimate if the individual will be subsampled.

Steps:

1. You must have an experienced estimator.
2. The estimator must record each individual with no information on which will subsampled.
3. Some small proportion of the estimated individuals is selected randomly for actual measurement.
4. A correction ratio is formed between the estimated values and the actual values on the subsampled individuals.
5. The correction ratio is applied to all estimated values, which are then tabulated.

Advantages:

1. Much quicker to implement that measuring all individuals.
2. Can be considered a statistically sound way to "guess."

References

Grosenbaugh, L. R. 1965. Three-Pee sampling theory and program "THRP" for computer generation of selection criteria. USDA Forest Service. Pacific Southwest Forest and Range Experiment Station, Research Paper. PSW-21. 53 pp.

Avery , T. E. and H. E. Burkhart. 1994. Forest Measurements. McGraw-Hill, New York. 408 p. Chp 12.