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MemoIntroduction:Since the higher education market is clearly grouped we have to use stratified random sampling So that each strata (group) gets properly represented by the sample selected and give a more precise estimate of the entire population.In stratified random sampling the entire population is divided into strata and samples are picked from each strata. There can be three types of stratified random samplingProportionateDisproportionateOptimalProportionate stratified random sampling: the ratio of-the number of elements chosen from a particular stratum (n1) to the total number of elements in that particular stratum(N1) is equal to the ratio of -the number of elements chosen from all other strata to the total number of elements in those strata.
n1/N1=n2/N2=---------nn/NnDisproportionate stratified random sampling: the ratio of the number of elements chosen from a particular stratum (n1) to the total number of elements in that particular stratum (N1) is not equal to the ratio of the number of elements chosen from all other strata to the total number of elements in those strata.n1/N1 not equal to n2/N2This is used when separate statistical analysis for particular strata are required.Suitable ratios are thereafter used to restore original proportions.
Optimal stratified random sampling: due to cost concerns the researcher might want to achieve maximum accuracy that is minimum variance while keeping the costs minimum. This can be done when high degree of precision is not required but only a fair amount of idea can serve the purpose.Advantages and Disadvantages of the above three methods:AdvantagesDisadvantagesProportionate stratified random sampling The sample represents the true population. Disproportionate stratified random sampling: the ratio of the number of elements chosen from a particular stratum (n1) to the total number of elements in that particular stratum (N1) is not equal to the ratio of the number of elements chosen from all other strata to the total number of elements in those strata.
Optimal stratified random sampling: due to cost concerns the researcher might want to achieve maximum accuracy that is minimum variance while keeping the costs minimum. This can be done when high degree of precision is not required but only a fair amount of idea can serve the purpose. Since in this case a fair enough estimate is required as the company is just entering the book market and lack of precision will not cause harm as it is not a quality check but only a overall market estimate, optimal stratified random sampling is recommended.
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