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Stratified sampling is actually not a new [[lectuenotes:Sampling design and plot design|sampling design]] of its own, but a procedural method to subdivide a ...chive a higher [[accuracy and precision|precision]] with the same [[sample size]]. Beside statistical issues there are further arguments for stratification

...chtete Stichprobe) ist kein eigentliches [[Lectuenotes:Sampling design and plot design| Stichprobenverfahren]], sondern eine Vorgehensweise um eine [[Lectu Bei der Herleitung des nötigen [[Lecturenotes:Sample size|Stichprobenumfang]]s, der immer durch den vogegebenen zulässigen Fehler, d

...refers to the number of samples) while the [[Sampling intensity vs. sample size|sampling intensity]] is a relative value. ...ample size cannot be answered directly. But the question about what sample size is necessary to derive an estimation with a predetermined [[Accuracy and pr

...h a sample point we define a certain area that is the [[Plot design|sample plot]] where the observation one makes on this area is assigned to the respectiv ... sampled and of which the sample frame consists are typically the [[Sample plot|sample plots]] and not single trees! In other words: one selects areas in t

...[[Lecturenotes:population|population]] in which sampling is conducted. The size of the polygons is an expression of the [[inclusion probability|selection p ...ha that it represents once it is included in a sample under the stipulated plot design. By intersecting all buffers one can tessellate the area in single p

...uy test questions that might be relevant in context of planning a suitable plot design in national forest inventories or for the test in forest inventory: * Explain why a major statistical planning criterium for the choice of a [[plot design]] is to capture as much of the given variability of the target varia

...rces available to measure <math>n=10</math> sample plots. The small sample size led to a fairly high value of the estimated [[error variance]]. ... 25 m x 25 m out of each original plot. By that, you increase the [[sample size]] to the fourfold and, thus, reduce the error variance.

... sampling design but just a variation of [[Lectuenotes:Sampling design and plot design|response design]]: The major point in cluster sampling is that for e ...ct this observation unit of 6. In fact, most basic [[:Category:Plot design|plot designs]] as used in [[forest inventory]] can be viewed as cluster plots, w

...ly selected. Randomization is a design component of [[Sampling design and plot design|sampling design]]. The estimators for [[simple random sampling]] are ... text=The lack of randomization cannot be compensated by increasing sample size!}}

...pretend to be blind; and so we do on the some times long way to the sample plot! It is hypothesized that this is a waste of resources and that there must b ... that specific topic. Often, the simplest solution is to increase [[sample size]] in order to increase the probability to encounter the rare objects; howev

...s]] perform differently for the same population and with the same [[sample size]]. ...nterested in the y values. The <math>x</math> values are a measure for the size (area) of the strips; this will later be used in the context of other estim

...get objects]], so that the parametric mean density in terms of objects per plot is ... therefore <math>m_i = 1</math>, <math>yi = 0</math>; they are networks of size 1.

...plot” that is being laid out then is a large [[cluster sampling|cluster plot]] consisting of numerous sub-plots – that is, all the sample points on th ...n make an unbiased estimation of mean and variance from a random sample of size <math>n = 1</math>. For the estimation of the mean, there is no problem at

...plots; here, the ratio estimator may be apllied for estimation using plot size as covariable(de Vries 1986<ref>de Vries, P.G., 1986. Sampling Theory for ...b|400px|'''Table 1''' The population of all possible systematic samples of size <math>n=10</math> drawn from the example population. There are only 3 pos

... plots; here, the ratio estimator may be applied for estimation using plot size as co-variable (DeVries 1986<ref>de Vries, P.G., 1986. Sampling Theory for ...s known (and vice versa). Therefore, if such a co-variable is there on the plot, it would make sense to also observe it and utilize the correlation to the

...plots; here, the ratio estimator may be applied for estimation using plot size as co-variable (DeVries 1986<ref>de Vries, P.G., 1986. Sampling Theory fo ... plots]]. One approximation to estimation is to imagine a virtual [[circle plot]] through the <math>k^{th}</math> tree, that is, a circle which has a radiu

... the entire area of interest. In any case, the error of estimating stratum size was small in this case.

Line sampling uses one-dimensional lines as [[plot design|observation units]], just as we may use for many purposes fixed area ...ndard procedure when determining probabilities: we must try and define the size of the total population of needles and then identify that part of the popul

...robability that element ''i'' is eventually (or included) in the sample of size ''n''. The [[Horvitz-Thompson estimator]] bases on the inclusion probabilit ... probability proportional to a meaningful variable. Imagine e.g. different plot sizes for different tree dimensions. If bigger trees are observed in larger

..., there is no point in sampling. We, obviously, need to find an ancillary size variable of which we know that the target variable is as highly correlated ...gure 2. The parametric variances, with probabilities proportional to strip-plot area, for the estimated total and the estimated mean, respectively, are as