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Normal Probability Distribution Stratified Sampling: Stratified Sampling

As usual, we determined the maximum permissible error, , and the coefficient corresponding confidence level. Furthermore, in stratified sampling also need to determine the type of affixation to be considered. Thus we get the different sample sizes:

• For half :

.

• For total :

.

• For proportion :

.

.

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Sample Size: Number

To determine the number of strata is commonly used expression:

being cost per unit cost per stratum. The problem with this formula is that it is not operational because it depends on the size of the sample.

In general the accuracy increases with the number of layers if these are well chosen, but it is not his number if produgar such increase does not compensate for the complications of calculation. Clearly the maximum number of layers must be to estimate the variances in each stratum, and is generally recommended to take less than 6 layers.

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Strata Stratified Sampling: Stratified Random Sampling

is given the name of affixation to sample size allocation between the different strata. Setting up different ways to spread the sample, among which four specialties:

• Uniform allocation: are taken every same, ie, are assigned the same number of units within each stratum This affixation favors the younger strata and large hurts:

• Proportional : In this case is proportional to the size of the stratum

with

.

All units have the same chance of being selected

• Allocation minimum variance or Neyman: In this type of affixation are chosen a way that minimizes the variance for a fixed . The problem is to minimize subject to . Therefore, the sample is divided as

.

• Optimal Allocation: Here is chosen so as to minimize the variance for a fixed cost . This cost is given by where is the cost per unit in stratum and is the initial cost. The allocation is:
  

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