Sampling design and plot design
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(New page: For any sampling study, there are three basic design components that must be worked and decided on: (1) '''sampling design''', (2) '''response design''' and (3) '''estimation design'''. Al...) |
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| − | For any sampling study, there are three basic design components that must be worked and decided on: (1) '''sampling design''', (2) '''response design''' and (3) '''estimation design'''. All three need to be clearly defined before implementing | + | For any sampling study, there are three basic design components that must be worked and decided on: (1) '''sampling design''', (2) '''response design''' and (3) '''estimation design'''. All three need to be clearly defined before implementing an inventory! |
;Sampling design: defines how the “observation units” are selected and how many. Various options of sampling designs are dealt with in [[:category:sampling design|the category sampling design]]. | ;Sampling design: defines how the “observation units” are selected and how many. Various options of sampling designs are dealt with in [[:category:sampling design|the category sampling design]]. | ||
Revision as of 10:43, 14 January 2009
For any sampling study, there are three basic design components that must be worked and decided on: (1) sampling design, (2) response design and (3) estimation design. All three need to be clearly defined before implementing an inventory!
- Sampling design
- defines how the “observation units” are selected and how many. Various options of sampling designs are dealt with in the category sampling design.
- Response design
- defines how the observation unit “responds”. It is also called plot design or observation design. In the forest inventory context, the response design defines the plot type to be used and the measurements that are to be taken on that plot. All in all, the response design describes what is to be done on the spot that had been selected in the sampling design.
- The estimation design
- defines the formula (the estimators) that are used for estimation. One is not free to choose any formula but the estimator needs to be compatible to both sampling and response design. It cannot be enough stressed how important it is to have the estimation design completely clear before starting to go out and collect data. There are too many cases in which data were collected according to some complex sampling or plot design - and at the end it was not known how to do a proper analysis of the data.
