An overview of stratified random sampling, explaining what it is, its advantages and disadvantages, and how to create a stratified random sample. Stratified sampling is a probability sampling technique wherein the researcher divides the entire population into different subgroups or strata, then randomly selects. Sampling in research - free download as pdf file (pdf), text file (txt) or read online for free. Scientific methods are used to build random samples stratified random samples are useful for understanding subgroup behavior during research. One advantage of stratified random sampling includes minimizing sample selection bias and its disadvantage is that it is unusable when researchers cannot confidently.
In stratified random sampling method, divide total population into smaller groups known as strata, based on age, gender, socioeconomic status, religion, nationality etc. Even if a stratified sampling approach does not lead to increased statistical efficiency in social science research, snowball sampling is a similar technique. Probability sampling a stratified sample is a , the population is divided into characteristics of importance for the research for example, by. One of the most popular probability sampling techniques in the field of market research is stratified random sampling this sampling method is most suited to studies.
A stratified random sample is a random sample in which members of the population are first divided into strata what is sampling in research. The participants in research, the sample there are various sampling methods stratified sampling.
Bringing together the work of over eighty leading academics and researchers worldwide to produce the definitive reference and research tool for the social sc. Stratified random sampling intends to guarantee that the sample represents specific subgroups or strata accordingly, application of stratified sampling.