- Long Answer Type Questions:
1.question- Distinguish between'random sampling and stratified sampling.
Clearly explaining the two in detail. Give examples of both
Answers
Explanation:
Simple random samples and stratified random samples are both statistical measurement tools. A simple random sample is used to represent the entire data population. A stratified random sample divides the population into smaller groups, or strata, based on shared characteristics.
The population is the total set of observations or data. A sample is a set of observations from the population. The sampling method is the process used to pull samples from the population.
Unlike simple random samples, stratified random samples are used with populations that can be easily broken into different subgroups or subsets. These groups are based on certain criteria, then randomly choose elements from each in proportion to the group's size versus the population.
This method of sampling means there will be selections from each different group—the size of which is based on its proportion to the entire population. But the researchers must ensure the strata do not overlap. Each point in the population must only belong to one stratum so each point is mutually exclusive.
Answer:
random sampling is that method in which each item of whole condition or universe has equal chance to select on the other hand stratified is that method in which population of diffrent strata or group have different features and some items are select from each strata so entire population get represent