Stratified sampling examples

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(Example 1)
(Example 1)
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!''fpc''
 
!''fpc''
 
!''<math>\sigma_h^2/n</math>''
 
!''<math>\sigma_h^2/n</math>''
!''var per stratum<math>fpc\sigma_h^2/n</math>''
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!''var per stratum<math>fpc*\sigma_h^2/n</math>''
 
!''var*<math>W_h^2</math>''
 
!''var*<math>W_h^2</math>''
 
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Revision as of 20:21, 16 December 2010

Example 1

This example shows stratified sampling by the example population from figure 1.

Figure 1 Example population (deVries 1986)

Imagine the example population of \(N=30\) elements be subdivided into three strata as in figure 2. Here, stratification has been done arbitrarily into three strata of size 14, 8 and 8. From this stratified population, we wish to take a sample of \(n=10\), taking \(n_1=4\) from the first stratum and \(n_2=n_3=3\) from the other two strata. The stratum parametric means and variances are given in table 1.

Table 1 Stratum parameters for the stratified example population.

Stratum \(N_h\,\) \(n_h\,\) \(\mu_h\,\) \(\sigma_h^2\,\)
1 14 4 6.29 3.49
2 8 3 10.13 4.86
3 8 3 5.38 2.48
Figure 2 Subdividing the example population (arbitrarily) in three strata, for illustration purposes

Calculation in stratified sampling is best done in tabular format, first per stratum and then combining the per-stratum results to the values / estimations for the entire population. The estimation of the mean is illustrated in Table 2 and results – as expected – in the parametric mean without stratification. Table 3 presents the calculation of the parametric error variance for \(n=10\) and the defined allocation of samples to the three strata.

Table 2 Calculation of parametric population mean from the parametric strata means.

Stratum Stratum mean Weight \((W_h)\) mean*weight
1 6.29 0.466667 2.9333
2 10.13 0.266667 2.7000
3 5.38 0.266667 1.4333
7.0667

Table 3 Calculation of parametric error variance of the estimated mean of the population for \(n=10\).

Stratum fpc \(\sigma_h^2/n\) var per stratum\(fpc*\sigma_h^2/n\) var*\(W_h^2\)
1 0.769230769 0.87244898 0.67111461 0.146154
2 0.714285714 1.61979167 1.15699405 0.082275
3 0.714285714 0.82812500 0.59151786 0.042063
\(var(\hat y)=\) 0.270492
Construction.png sorry: 

This section is still under construction! This article was last modified on 12/16/2010. If you have comments please use the Discussion page or contribute to the article!

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