Respuesta :
The population can be divided into strata so that the individuals in each stratum are as much alike as possible is the preferable condition to using stratified random sampling rather than simple ones.
As the name implies, simple random sampling involves only selecting individuals at random from the population. It just cares about sampling a representative sample of the population as a whole and makes no sub-classification assumptions about the population in question.
As the name suggests, stratified random sampling involves a stratified sample. The sampling is then carried out proportionally to each group's size in relation to the population size. For instance, if you have a population of red, green, and blue colored balls and you wish to sample the population according to colors, the colored groupings will act as strata and the sampling will be conducted on subgroups; this sort of sampling is known as stratified random sampling.
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