Difference between revisions of "Sampling And Statistics"
(New page: ==About sampling forest data== ==Estimations from plot sample data== Assume we have sampled ''n'' plots from a treatment unit (stand) with area ''A'' and that we want to estimate some sta...) |
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==About sampling forest data== | ==About sampling forest data== | ||
| − | ==Estimations from plot sample data== | + | ==Estimations of total values from plot sample data== |
| − | Assume we have sampled ''n'' plots | + | Assume we have sampled ''n'' plots in a treatment unit (stand). On each plots, all trees have been measured. The stand has area ''A'' and we want to estimate some stand variable ''Y'', given as a value per area unit ''Y<sub>ha</sub>''. Then the estimated value of ''Y'' is |
<math>\hat{Y}_{ha}} = \frac{\sum_{i=1}^n{y_i}}{\sum_{i=1}^n{a_i}}</math> | <math>\hat{Y}_{ha}} = \frac{\sum_{i=1}^n{y_i}}{\sum_{i=1}^n{a_i}}</math> | ||
where | where | ||
| − | <br><math> | + | <br><math>\hat{y}_i=</math>estimated value in plot ''i'', and |
<br><math>a_i=</math>inventoried area of plot ''i'' | <br><math>a_i=</math>inventoried area of plot ''i'' | ||
| − | + | We then compute the estimated value of ''Y'' by simply multiplying with ''A'' (assuming that ''A'' is known):<br> | |
| − | <math>\hat{Y | + | <math>\hat{Y}} = A\times\hat{Y}</math> |
| + | |||
| + | In a prognosis, growth is computed for each plot separately, one period at a time (although treatments may be coordinated between plots). A prognosis model often include some variables that describe the density of the tree cover. For example, total basal area and stem density are common variables in growth functions, expressed as basal area per ha (m<sup>2</sup>)/ha) and number of trees per ha (trees/ha). Therefore, it is practical to keep all density variables at the plot level to a per ha-value. | ||
| + | |||
| + | ==Estimations of variance from plot sample data== | ||
[[Category:Sampling]] | [[Category:Sampling]] | ||
[[Category:Statistics]] | [[Category:Statistics]] | ||
Revision as of 13:36, 30 August 2008
About sampling forest data
Estimations of total values from plot sample data
Assume we have sampled n plots in a treatment unit (stand). On each plots, all trees have been measured. The stand has area A and we want to estimate some stand variable Y, given as a value per area unit Yha. Then the estimated value of Y is
where
estimated value in plot i, and
inventoried area of plot i
We then compute the estimated value of Y by simply multiplying with A (assuming that A is known):
In a prognosis, growth is computed for each plot separately, one period at a time (although treatments may be coordinated between plots). A prognosis model often include some variables that describe the density of the tree cover. For example, total basal area and stem density are common variables in growth functions, expressed as basal area per ha (m2)/ha) and number of trees per ha (trees/ha). Therefore, it is practical to keep all density variables at the plot level to a per ha-value.