Stratified sampling examples

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(Example 1)
(Example 1)
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[[File:5.2.6-fig74.png|right|thumb|300px|Figure 1:  Illustration why  stratification is most efficient when the ''strata  means'' are as  different as possible]]
 
[[File:5.2.6-fig74.png|right|thumb|300px|Figure 1:  Illustration why  stratification is most efficient when the ''strata  means'' are as  different as possible]]
 
[[File:5.2.6-fig75.png|right|thumb|300px|Figure 2:  Subdividing the  example population (arbitrarily) in three strata, for  illustration  purposes]]
 
  
 
Imagine the example population of <math>N=30</math> elements be subdivided into three strata as in figure 1. 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 <math>n=10</math>, taking <math>n_1=4</math> from the first stratum and <math>n_2=n_3=3</math> from the other two strata. The stratum parametric means and variances are given in Table 1.                 
 
Imagine the example population of <math>N=30</math> elements be subdivided into three strata as in figure 1. 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 <math>n=10</math>, taking <math>n_1=4</math> from the first stratum and <math>n_2=n_3=3</math> from the other two strata. The stratum parametric means and variances are given in Table 1.                 
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!''Stratum''
 
!''Stratum''
 
!''Stratum mean''
 
!''Stratum mean''
!''Weight <math>W_h\,</math>''
+
!''Weight <math>(W_h)</math>''
!''mean<math>*\,</math>weight''
+
!''mean*weight''
 
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|1
 
|1
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</div>
 
</div>
  
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[[File:5.2.6-fig75.png|right|thumb|300px|Figure 2:  Subdividing the    example population (arbitrarily) in three strata, for  illustration    purposes]]
  
 
{{Construction}}
 
{{Construction}}
  
 
[[Category:Forest Inventory Examples]]
 
[[Category:Forest Inventory Examples]]

Revision as of 18:49, 16 December 2010

Example 1

Figure 1: Illustration why stratification is most efficient when the strata means are as different as possible

Imagine the example population of \(N=30\) elements be subdivided into three strata as in figure 1. 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





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
Figure 2: Subdividing the example population (arbitrarily) in three strata, for illustration purposes
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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