Skip to Main Content
Estimating two-way tables based on forest surveysAuthor(s): Charles T. Scott
Source: In: Hansen, Mark; Burk, Tom, eds. Integrated tools for natural resources inventories in the 21st century. Gen. Tech. Rep. NC-212. St. Paul, MN: U.S. Dept. of Agriculture, Forest Service, North Central Forest Experiment Station. 234-238.
Publication Series: General Technical Report (GTR)
Station: North Central Research Station
PDF: View PDF (312.29 KB)
DescriptionForest survey analysts usually are interested in tables of values rather than single point estimates. A common error is to include only plots on which nonzero values of the attribute were observed when computing the variance of a mean. Similarly, analysts often exclude nonforest plots from the analysis. The development of the correct estimates of forest area, attribute totals, and their means over the area of interest is described. Program TabGen was written to perform these calculations correctly assuming simple random sampling, stratified random sampling, or double sampling for stratification.
- Check the Northern Research Station web site to request a printed copy of this publication.
- Our on-line publications are scanned and captured using Adobe Acrobat.
- During the capture process some typographical errors may occur.
- Please contact Sharon Hobrla, firstname.lastname@example.org if you notice any errors which make this publication unusable.
- We recommend that you also print this page and attach it to the printout of the article, to retain the full citation information.
- This article was written and prepared by U.S. Government employees on official time, and is therefore in the public domain.
CitationScott, Charles T. 2000. Estimating two-way tables based on forest surveys. In: Hansen, Mark; Burk, Tom, eds. Integrated tools for natural resources inventories in the 21st century. Gen. Tech. Rep. NC-212. St. Paul, MN: U.S. Dept. of Agriculture, Forest Service, North Central Forest Experiment Station. 234-238.
- Conducting tests for statistically significant differences using forest inventory data
- Influence of tree spatial pattern and sample plot type and size on inventory
- An application of quantile random forests for predictive mapping of forest attributes
XML: View XML