Howtosignalprocessing
For example, a stratum could be large supermarkets, which may only account for 20% of all grocery stores – although they account for 80% of grocery sales. In this case, a disproportionate sample would be used to represent the large supermarkets to reflect their sales (i.e. 80%) rather than the number of stores.
- How do you calculate disproportionate sampling?
- What is a disproportionate systematic sample?
- What is the difference between proportionate and disproportionate stratified random sampling?
- What is an example of proportionate stratified sampling?
How do you calculate disproportionate sampling?
Proportionate and Disproportionate Stratification
For example, if the researcher wanted a sample of 50,000 graduates using age range, the proportionate stratified random sample will be obtained using this formula: (sample size/population size) × stratum size.
What is a disproportionate systematic sample?
A disproportionate sample ensures that you have an adequate number for analyzing even the smallest groups in a population. Using this method, the researchers can evenly divide the total sample size between the subgroups or use different proportions that make sense for their study.
What is the difference between proportionate and disproportionate stratified random sampling?
If the same sampling fraction is used in each stratum this is termed 'proportionate stratified sample'; if the sample fraction is not the same in each stratum this is termed 'disproportionate sampling'. More commonly the latter would be described as 'over-sampling of one or more sub-groups'.
What is an example of proportionate stratified sampling?
For example, one might divide a sample of adults into subgroups by age, like 18–29, 30–39, 40–49, 50–59, and 60 and above. To stratify this sample, the researcher would then randomly select proportional amounts of people from each age group.
