【正文】 rat to sample the potential cluster. This additional nonrandom sampling requires special formulas to estimate abundance without bias. Systematic sampling is easier to apply in the field than random sampling, but may produce biased estimates of means and confidence limits if there are periodicities in the data. In field ecology this is usually not the case, and systematic samples seem to be the equivalent of random samples in many field situations. If a gradient exists in the ecological munity, systematic sampling will be better than random sampling for describing it.Systematic Sampling? What is the likelihood that problems like periodic variation will occur in actual field data? Milne(1959) attempted to answer this question by looking at systematic samples taken on biological populations that had been pletely enumerated. He analyzed data from 50 populations and found that, in practice, there was no error introduced by that a centric systematic sample is a simple random sample, and using all the appropriate formulas from random sampling theory. Step 1. Calculate the average abundance of each of the works: () where =Average abundance of the ith work =Abundance of the anism in each of the k quadrats in the ith work =Number of quadrats in the ith wrok Step 2. From these values we obtain an estimator of the mean abundance as follows: () where Unbiased estimate of mean abundance from adaptive cluster sampling Number of initial sampling units selected via random samplingIf the initial sample is selected with replacement, the variance of this mean is given by: () where Estimated variance of mean abundance for sampling with replacement and all other terms are as defined above.If the initial sample is selected without replacement, the variance of the mean is given by: () where N = Total number of possible sample quadrats in the sampling universeThe example shown in Figure . in the initial random sample of n = 10 quadrats, from equation(). plants per quadratSince we were sampling without replacement, we use equation () to estimate the variance of this mean:We can obtain confidence limits from these estimates in the usual way:For this example with n = 10, for 95% confidence limits , and the confidence limits bee:or from to plants per quadrat. When should one consider using adaptive sampling? Much depends on the abundance and the spatial pattern of the animals or the plants being studied. In general the more clustered the population and the rarer the anism, the more efficient it will be to use adaptive cluster sampling .Thompson(1992) shows, in Figure ,that adaptive sampling is about 12% more efficient than simple random sampling for n = 10 quadrats and nearly 50% more efficient when n = 30 quadrats. In any particular situation it may well pay to conduct a pilot experiment with simple random sampling and adaptive cluster sampling to determine the size of the resulting variances.序貫抽樣法的基本原理序貫抽樣法的基本原理? 特點 :在抽樣時不預先指定子樣容量 ,而是要求給出一組停止采樣的規(guī)則 .檢驗的步驟檢驗的步驟拒絕則接受拒絕拒絕令例：東亞飛蝗蝗蝻的序貫抽樣，田間分布屬負二項分布，其公共 k值為 ，規(guī)定：每平方丈（ 1丈 =10/3米）平均蟲口在 1頭以下為輕度發(fā)生； 23頭為中等發(fā)生； 5頭以上為嚴重發(fā)生。于是有以下假設(shè)檢驗： （ 1）發(fā)生程度在輕度與中等之間 H0:平均蟲口密度 D≦ 1頭 /平方丈為輕度發(fā)生 H1:D≧ 2頭 /平方丈為中等發(fā)生 （ 2）發(fā)生在中等與嚴重之間 H0 ： D≦ 3頭 /平方丈為中等 H1: D≧ 5頭 /平方丈為嚴重常數(shù) 發(fā)生程度 發(fā)生程度輕度 中等 中等 嚴重Ho H1 H1 H2謝謝觀看 /歡迎下載BY FAITH I MEAN A VISION OF GOOD ONE CHERISHES AND THE ENTHUSIASM THAT PUSHES ONE TO SEEK ITS FULFILLMENT REGARDLESS OF OBSTACLES. BY FAITH I BY FAITH