Ultimate Sampling Guide
Finding the correct representative sample that resembles your target audience can lead to improved insights and lowers the chances of making errors.
Download the guide to understand step-by-step process of selecting the best sample for your next survey research
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Stratified Random Sampling is a probability sampling method found in market research software that uses a two-step process to select the sample group. The population is first divided into homogeneous subpopulations, or stratas, that are mutually exclusive and collectively exhaustive. This means that every element in the population must be assigned to only one stratum, and there shouldn’t be any overlap of elements across the stratas. The population is divided into different stratas on the basis of some stratification variables, such as income or domicile, for example.
After the elements have been divided into their respective stratas, SRS (simple random sampling) can be employed in market research studies to choose elements from each stratum to be a part of the sample group. As these elements are selected probabilistically, each element in the population has an equal and known chance of being selected. This is why stratified random sampling is a type of probability sampling. In theory, only SRS should be used to select elements from stratas, however in practice, researchers sometimes use other sampling methods such as systematic random sampling.
Download the guide to understand step-by-step process of selecting the best sample for your next survey research
Stratified random sampling is a sampling method that divides the target population into homogeneous groups before using SRS to select elements from each strata to be a part of the sample group.
Stratified Random Sampling is divided into two broad categories. They are as follows:
In proportionate stratified sampling, the sample size drawn from each stratum is proportionate to the stratum’s size in relation to the total population. Therefore, once the sample size is known, researchers calculate the percentage or proportion of each stratum in relation to the size of the target population. Once each stratum’s relative size is known, a sample size for each stratum can be determined. Once this is done, simple random sampling can be used to select random elements from each stratum. This method of sampling is easier, quicker, and more straightforward than disproportionate stratified sampling.
This method is used because larger stratas, or subpopulations, tend to have larger standard deviations (in regard to the characteristics of the stratified variables chosen) and hence to increase precision of the research, larger sampling sizes must be chosen from these stratas.
In disproportionate stratified sampling, on the other hand, the sample size chosen from each stratum is proportionate to the relative size of the stratum and to the standard deviation in the distribution of the characteristics among the elements in that stratum. The sample units from each stratum are determined by the researcher and their study’s rationale.
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