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This study employed proportionate stratified sampling in selecting the sample.
A multistage stratified random sampling design was employed in selecting the sample of 425 farmers.
The method of random sampling was used for selecting the sample size of 200.
The stratification process of selecting the sample input data ensures that random rows are selected.
In selecting the sample households for the survey, a multistage sampling procedure was employed.
Our approach is based on the idea of selecting the sample subset for removal in a manner which minimizes the associated loss of information which we formalized using a Bayesian framework.
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Thus the method optimized the contrast resolution by adaptively selecting the samples of the excitation.
The procedure that we use for selecting the samples as follows: 1.
The retrieved genes can be ranked in a way similar to the class ranking method used for pathway ranking, using the subset of data for these genes derived from the intermediate result file created when selecting the sample-level differentiated genes as described above.
One criterion for selecting the samples examined here was their potential for maintaining historically high levels of reciprocal gene flow.
This observation forms the basis for procedures used to select the sample size.
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